Measurements and Models of Oceanic O2 and CO2 Fluxes

Mark Battle (Bowdoin College)Sara Mikaloff Fletcher (UCLA)Michael Bender (Princeton)

Ralph Keeling (SIO) Nicolas Gruber (UCLA)

Pieter Tans (NOAA/CMDL)Melissa B. Hendricks (Princeton) David T. Ho (Princeton/Columbia)

Carrie Simonds (Bowdoin College)

Robert Mika (Princeton)Andrew Manning (SIO)

Bill Paplawsky(SIO)

AGUFall 2004

OS11C-08

Funding from:NSF

NOAA GCRPBP-Amoco

AGU poster Fall

2003 A52B-0793

On the agenda:

• What is APO?• Historical context• Our dataset• From sparse data to meridional

gradients• Modeling• Data-model comparison

Atmospheric Potential Oxygen

APO O2 + 1.1 CO2

APO changes solely due to oceanicprocesses*

*This is almost true

1.4

1.1

1.4

1.1

Atmospheric Potential Oxygen

APO O2 + 1.1 CO2

APO responds to oceanic O2 & CO2 fluxes

Land biota doesn’t change APO

Fossil fuels change APO a little

In the beginning…

Stephens et al., 1998

Models don’t getinterpolar gradientright (physics?)

Equatorial datawould be nice.

The next chapter…

Gruber et al., 2001

Eliminate BGCModel.

Results seem Independent ofOcean physics

Equatorial dataWould be nice.

We have equatorial data!

Sampling locations used in this work

Ships of opportunity

NOAA ship Ka’imimoana

Uneven spatio-temporal data density

Uneven spatio-temporal data density

Annual-mean gradients from sparse data?

2-D interpolation (latitude and time):

Create gradients at specific times through year

Average the gradients over climatological year

3 examples of gradients…

A weighted average of all gradients

Annual-mean gradients from sparse data?

2-D interpolation (latitude and time):

Create gradients at specific times through year

Average the gradients over climatological year

Seasonal Cycles:

Sine fits to data at each sampling latitudeAnnual means from sine fits

Annual means from seasonal cycles

New data deserve a new model

•Aseasonal O2: Ocean inversion (Gruber 2001)•Aseasonal N2: Heat inversion (Gloor 2001)•Oceanic CO2: pCO2 (Takahashi 1999)•Seasonal O2 and N2: Ocean heat fluxes (Garcia and Keeling 2001)•FF CO2 and O2: CDIAC (Marland 2000)•Atmospheric Transport: TM3.8•Winds: NCEP 1995 – 2000 (repeated and averaged)

Data-model comparison: 2-D interpolation

Data-model comparison: seasonal cycles

Is this different from old models?

The models really are different!

What has changed?

• Atmospheric Transport:– Was GCTM– Is now TM3

• Seasonal O2 & N2:

– Was Najjar & Keeling/Esbensen & Kushnir

– Is now Garcia and Keeling

In summary…

• Data coverage much greater• Equatorial “bulge” exists• Interpolar gradient smaller• Newest model gives much better overall

agreement with data• Past disagreements primarily due to

atmospheric transport• Disagreement persists at SYO, SAB and

CBA• Watch for a publication soon.

UCLA model annual mean APO

Merging PU & SIO datasets

Problems at Cold Bay

Time slices: Data

Time slices: Model

Data quality at Sable Island