Session on Simulating variability of air-sea CO2 fluxes

CarboOcean final meeting, Os, Norway, 5-9 October 2009

Funding: EU (GOSAC, NOCES), NASA, DOE, Swiss NSF, CSIRO

R. Matear (CSIRO, Hobart, Australia) :Impact of Historical Climate Change on the Southern Ocean Carbon Cycle

J. Orr (LSCE, Gif-sur-Yvette, France)Effects of forcing and resolution on simulated variability of air-sea CO2 fluxes

Effects of forcing and resolution on simulated variability of air-sea CO2 fluxes

CarboOcean final meeting, Os, Norway, 5-9 October 2009

Funding: EU (GOSAC, NOCES), NASA, DOE, Swiss NSF, CSIRO

J. Orr (LSCE)

Contributors: LSCE - J. Simeon, M. Gehlen, L. BoppLEGI (Grenoble) – C. Dufour, B. Barnier, J. LeSommer, J.-M. Molines

Outline

• Hints from North Atlantic (Raynaud et al., 2006)

• Hints from transient tracer simulaitons (Lachkar et al., 2007)

• Forcing

• Resolution

BATS: Sea-air CO2 flux anomalies (12-mo running

mean)

Why general underprediction? “Data” errors? Low horizontal

resolution (near west. boundary)

Weak Forcing (atm. reanalysis)

o from aboveo affects lateral lags

Raynaud et al., 2006 (Ocean Science, 2, 43-60)

NCEP underestimates real wind speed variability

Interannual var. in wind speed:

NCEP < (1/3) ERA40

NCEP wind speeds lower than WOCE ship track winds

NCEP atm. transport variability only half that observed (Waliser et

al., 1999)

North Atlantic

Smith et al. (2001, J. Climate)

Raynaud et al. (2006, Ocean Science)

HOT: Sea-air CO2 flux anomalies (12-mo running

mean)Raynaud et al., 2006 (Ocean Science, 2, 43-60)

LSCE testing importance of resolving eddies (global model):

Non-eddying 2° Eddying ½°

Data*de Boyer Montégut (2004, JGR)

• Mixed layer depth

non-eddying

non-eddying + GM

eddying + GM eddying

CFC-11 burden (integrated vertically & zonally)

*Lachkar et al (2007, Ocean Science)

Zonal In

tegra

l of

CFC

-11

(M

mol degre

e-1)• CFC-11 inventory

Improvements:

Southern Ocean carbon sink – different stories

• Le Quéré et al. (2007): slower than expected [coarse-resolution model, NCEP forcing]

• Matear and McNeil (2008): not slower [another coarse-res. model, NCEP forcing]

• Sarmiento et al. (2009): slower [4 coarse-res. models, NCEP forcing]

• Bopp (2009): [coarse-res. model]– slower with NCEP forcing; – not slower with ERA40

Changes in observed T across ACC reveal fingerprint of anthropogenic climate change

Boening et al. (2008, Nature Geoscience)

52 447 Argo Profiles

Mean for neutral densities 26.9 to 27.7

Observed T trend on density surfaces

• Bin by dynamic height (0.09 levels)

• Average

• Remap onto mean bin latitudes

Boening et al. (2008, Nature Geoscience)

Observed trends on depth surfaces

Temperature Salinity

Boening et al. (2008, Nature Geoscience)

In forcing ocean GCM’s, there is much room for artistry … and error

• Atmospheric surface variables

• Bulk formulas

L. Brodeau, B. Barnier, T. Penduff, J.-M. Molines (2009) An ERA40-based atmospheric forcing for simulations and reanalyses of the global ocean circulation between 1958 to present, submitted.

Large uncertainties

Building adequate forcing requires huge effort

• Strategy to blend – corrected ERA40 surface atmospheric state fields (wind, air

temperature, humidity) with – satellite products (ISCCP for radiation, CMAP for precipitation)

processed by Large & Yeager (2004) for CORE data set.

• Procedure:– Replace CORE’s NCEP with ERA40 (surface T, humidity, wind)

• Extend ERA40 until 2004 with ECWMF operational product• Correct major ERA40 flaws (biases, inter-annual discontinuities)

– Adjust CORE shortwave radiation and precipitation products– Quantify changes in forcing with a series of 1958-2004 interannual

2° (ORCA2) simulations assess impact of every forcing variable on the model solution.

Example from high-res. ocean modeling consortium (DRAKKAR DFS3, DFS4):

DFS4.1 forcing in 2° model (NEMO/ORCA2)

T trend S trend

Den

sity

(σ

)D

ep

th (

m)

LSCE simulations (J. Simeon et al.) with LEGI forcing (DRAKKAR DFS4.1)

NCEP-2 forcing in 2° model (NEMO/ORCA2)

T trend S trend

Den

sity

(σ

)D

ep

th (

m)

LSCE simulations (J. Simeon et al.) with NCEP-2 forcing

Different forcing results in different air-sea fluxes of natural CO2 during pre-satellite era

NEMO/ORCA2 model

Southern Ocean (south of 45°S)Ocean efflux

Preliminary comparison of resolution (2° vs. 0.5°) + many other differences:

Conclusions

• Different forcing fields – strengthen ties to evolving developments of ocean circulation modeling community

• Different resolutions – ibid

• Different models – need more concerted evaluation, comparison & strategy

• Different BGC components – minimum complexity to properly simulate interannual variability & trends?

Conclusions:• Arctic surface [CO3

2-]: high in summer, low in winter (as elsewhere: Bering Sea, Norwegian Sea, Southern Ocean)

• High summertime [CO32-] from

• Biologically driven increase (from DIC drawdown) overwhelms

• Physically driven decrease (freshening, i.e., dilution)

• Opposite trend in models with excessive fresh-water input

• Chukchi Sea surface water:– observed seasonal amplitude (≥12 μmol kg-1)

(equivalent to past 30+ years of transient change)– That annual cycle + Beringia 2005 summer data, yields

Wintertime Ωa < 1 already by 1990 (pCO2 atm = 354 ppmv), i.e., 30 years sooner than summertime observations