REMOTE SENSING OF SOUTHERN OCEAN AIR-SEA CO 2 FLUXES

REMOTE SENSING OF SOUTHERN OCEAN AIR-SEA CO2 FLUXES

A.J. Vander WoudePete Strutton and Burke Hales

Global CO2 flux

Takahashi et al., DSR I, 2009: 4.5 million data pointsTakahashi et al., DSR I, 2009: 3 million data points

Global CO2 data coverage

Southern Ocean & atmospheric CO2

Observations versus models

Gruber et al. 2009

In some places there are no observations:pCO2 from co-varying parameters is a way forward

We can investigate smaller spatial scales:Limited by the resolution of the satellite data

(kilometers), not sparse observations (~102 to 103 km)

We can investigate seasonal and interannual variability:Links to long term changes in forcing: Southern Ocean winds

Why this may be better than observational methods?

Steps to Create Predictive Satellite Algorithms: West Coast Example

Remote Sensing ClimatologyMonthly Data

Chlorophyll a (mg/m3)

Wind speed (m/s)

Sea Surface Height (cm)

OI Reynolds Sea Surface Temperature (°C)

Sea Surface Height: AVISO Multimission 1999-2008

Chlorophyll: SeaWiFS 1999-2002, MODIS/Aqua + SeaWiFS Merged 2003-2007, MODIS/Aqua 2007-2008

Wind speed: QuickSCAT 1999-2008

OI Reynolds SST: AVHRR 1999-2002, AVHRR+AMSR 2002-2008

Steps to Create Predictive Satellite Algorithms

Probablistic Self-Organizing Maps

January February March

region number

There is some correspondence between SOM regions and the fronts

Spatial and temporal coherence of the fronts from month to month

Longhurst 1998

Overview of Predictive Satellite Algorithms

A

Alkalinity and DIC from the McNeil climatologies

Optimizing: Alk, DIC, Ti, Heating/Mixing term, Tcr

Chlorophyll term

Each has a constant, longitude, latitude & seasonal signal

Powell’s Optimization

pCO2 Results & Accuracy of Regional Model

SummerSpring

Autumn Winter

pCO2 (ppm) pCO2 (ppm)

pCO2 (ppm) pCO2 (ppm)

OboObserved

Pred

icte

d

Region 4May and June

Red is a source to the atmosphere

White is at atmospheric

Blue is a sink, into the ocean

Conclusions and future work

Satellite algorithms offer a way to fill gaps and better quantify spatial and temporal variability of CO2

Next:-- Finishing the monthly algorithms, by region as well as Seasonal and interannual variability and produce maps of CO2 fluxes for the Southern Ocean

-- More rigorous comparison with climatologies andmodels.

Thank you!

• NASA for funding for this project

• Maria Kavanaugh for her help with the PRSOM analysis and Ricardo Letelier’s lab use of their PRSOM/HAC code

CDIAC in situ pCO2 Coverage

1.4 million data points in the Southern Ocean, south of 40° S

SO GasEx observations and satellite predictions

SO GasEx observations and McNeil predictions

SO GasEx observations and Takahashi predictions

Southern Ocean & atmospheric CO2

Gruber et al. 2009

Contemporary sink of:

.1 to .5 PgC/yr (circulation models & atm and oceanic inversion models)

.5 to .7 PgC/yr(pCO2 measurements, Takahashi et al. 2002)

.15 to .65 PgC/yr(empirical estimated pCO2, McNeil et al., 2007)