Ecosystem composition and CO2 flux variability

1
Ecosystem composition and CO2 flux
variability
Corinne Le Quéré Max-Planck-Institut für
Biogeochemie, Jena, Germanynow at University of
East Anglia/British Antarctic Survey with Erik
T. Buitenhuis and Olivier Aumont
2
CO2 budget (PgC/y)
1980-2000
5.9
Fossil fuel emissions
3.2
Atmospheric increase
0.9
Land sink
1.8
Ocean sink
3
CO2 budget (PgC/y)
1980-2000
100
Fossil fuel emissions
54
Atmospheric increase
15 (42)
Land sink
31
Ocean sink
4
DOWN
Anthropogenic C
55
depth (m)
0
60S
60N
umol/kg
Sabine et al., 2004
5
UP
DOWN
Total C
Anthropogenic C
2400
55
depth (m)
0
1800
60S
60N
60S
60N
umol/kg
Sabine et al., 2004 Key et al., 2004 CDIAC
6
UP
DOWN
Total C
Anthropogenic C
2400
depth (m)
1800
60S
60N
60S
60N
umol/kg
Sabine et al., 2004 Key et al., 2004 CDIAC
7
oceanic carbon cycle
CO2
90
chemical reactions
8
(slide from J. Sarmiento)
9
UP
DOWN
biological export production
winter mixed layer depth
Schlitzer 2001 World Ocean Atlas 2001
10
UP
DOWN
chemical reactions
11
Photosynth. Bacteria, N2-fixers
Calcifiers,
DMS-producers,
autothr. dinoflagellates
diatoms
Ciliates, heterotr. flagellates
Copepods, euphausids
Salps, pteropods
12
bacteria
phyto-plankton
zoo-plankton
13
NPZD model
CO2 flux
PO4
Phyto
DOC
Zoo
POC
export
14
Geider et al., 1997
15
PISCES model (NNNPPZZDDD)
CO2 flux
big
Aumont et al., 2003
16

• can we constrain complex ecosystem models?

17

• yes

18
Ocean Physical Model

• OPA General Circulation model (Madec et al.
  2001)
• NCEP daily forcing
• 0.5-1.5ox2o resolution
• 10 vertical levels in top 100 m (30 total)
• Thermodynamic Sea Ice model
• (Louvain La Neuve,
  Fichefet et al.)
• Nutrients restored under the Mixed layer
  (50ltmldlt100)

19
Meso zooplankton rates (d-1)
PISCES-T model
1.4
3.0
growth
growth
chl
T
0.6
2.5
mortality
respiration
T
T
Buitenhuis et al., in prep. Hirst and Kiorboe
2002 Ikeda 2001 Hirst and Bunker 2003
20

• can we evaluate complex ecosystem models?

21

• yes

22
Surface chla (mgChl/m3)
PISCES
Observations (SeaWiFS)
PISCES-T
23
export of C (mol/m2/y)
PISCES
from observations (Schlitzer 2001)
PISCES-T
24
Meso-zooplankton (uM)
PISCES
Observations (WOA, FSU, CPR)
PISCES-T
25
Interannual chla variability (mgChl/m3)
PISCES
Observations (SeaWiFS)
0.1
PISCES-T
26
Interannual chla variability (percent)
PISCES
Observations (SeaWiFS)
60
40
PISCES-T
20
27

• what do complex ecosystem models bring?

28

• freedom

29
Interannual chla variability (mgChl/m3)
NPZD
Observations (SeaWiFS)
DGOM
PISCES-T
30
Dynamic Green Ocean Model (NNNPPPZZDDD)
CO2 flux
big
Buitenhuis et al., in prep.
31
Surface chla (mgChl/m3)
NPZD
Observations (SeaWiFS)
DGOM
PISCES-T
32
Interannual chla variability (mgChl/m3)
NPZD
Observations (SeaWiFS)
DGOM
PISCES-T
33
Interannual chla variability (percent)
NPZD
Observations (SeaWiFS)
DGOM
PISCES-T
34
Surface chla (mgChl/m3)
NPZD
Observations (SeaWiFS)
0.6
0.3
Interannual standard deviation
DGOM
PISCES-T
0.3
0.3
mean
35
NPZD
Observations
Log (meso-zoo/chl)
PISCES-T
DGOM
Log (chl)
36

• can complex ecosystem models help our
  understanding?

37

• can complex ecosystem models bring new
  information?

38

• does it matter for CO2 fluxes?

39
CO2 sink (PgC/y)
4
0
10
Export (PgC/y)
14
40
oceanic carbon cycle
CO2
90
chemical reactions
41
oceanic carbon cycle
CO2
90
1.8
biological activity
chemical reactions
45
Fe
NO3
Si
PO4
NH4
DMS
34
Calcifiers
Nano phytoplankton
DMS producers
N2 fixers
Silicifiers
CaCO3
DOM
33
11
11
physical transport
42
oceanic carbon cycle
CO2
90
1.8 0.8
biological activity
chemical reactions
45
Fe
NO3
Si
PO4
NH4
DMS
341
Calcifiers
Nano phytoplankton
DMS producers
N2 fixers
Silicifiers
CaCO3
DOM
33
11
11-1
physical transport
43
CO2 budget (PgC/y)
1980-2000
100
Fossil fuel emissions
54
Atmospheric increase
15 (42)
Land sink
31
Ocean sink
44
conclusions

• simple ecosystem models are too tightly linked to
  ocean physics but easy to use
• complex ecosystem models are difficult to
  parameterize but add degrees of freedom
• both are needed

45
related posters

• Thursday Leticia Cotrim da Cunha, Impact of
  river sources of P, Si and Fe on coastal
  biogeochemistry
• Friday Manfredi Manizza, Bio-optical impact of
  phytoplankton on ocean physics and air-sea fluxes

46
Standard deviation in winter MLD
Observations (WOA 2001)
OPA model
47
PISCES
observations (WOA, FSU, CPR)
Log (meso-zoo/chl)
PISCES-T
Log (chl)
48
winter mixed layer depth
total C
2400
depth (m)
500
2000
60S
60N
latitude
umol/kg
240, 1185, 35525
49
MIT model
CO2 variability (Pg C/y)
OPA model
Hamburg model
(Peylin, Bousquet, Le Quéré et al., submitted)
50
northern sub-tropics
MIT model
OPA model
CO2 variability (mol/m2/y)
observations
(Peylin, Bousquet, Le Quéré et al., submitted)