Measurements and Models of Oceanic O 2 and CO 2 Fluxes Mark Battle (Bowdoin College) Sara Mikaloff Fletcher (UCLA) Michael Bender (Princeton) Ralph Keeling.

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Presentation transcript:

Measurements and Models of Oceanic O 2 and CO 2 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) AGU Fall 2004 OS11C-08 Funding from: NSF NOAA GCRP BP-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  O CO 2 APO changes solely due to oceanic processes* * This is almost true

Atmospheric Potential Oxygen APO  O CO 2 APO responds to oceanic O 2 & CO 2 fluxes Land biota doesn’t change APO Fossil fuels change APO a little

In the beginning…

Stephens et al., 1998 Models don’t get interpolar gradient right (physics?) Equatorial data would be nice.

The next chapter…

Gruber et al., 2001 Eliminate BGC Model. Results seem Independent of Ocean physics Equatorial data Would be nice.

We have equatorial data!

Sampling locations used in this work

Ships of opportunity

NOAA ship Ka’imimoana

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 latitude Annual means from sine fits

Annual means from seasonal cycles

New data deserve a new model Aseasonal O 2 : Ocean inversion (Gruber 2001) Aseasonal N 2 : Heat inversion (Gloor 2001) Oceanic CO 2 :  pCO 2 (Takahashi 1999) Seasonal O 2 and N 2 : Ocean heat fluxes (Garcia and Keeling 2001) FF CO 2 and O 2 : 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 O 2 & N 2 : –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