remote sensing of southern ocean air-sea co 2 fluxes
DESCRIPTION
REMOTE SENSING OF SOUTHERN OCEAN AIR-SEA CO 2 FLUXES. A.J. Vander Woude Pete Strutton and Burke Hales. Global CO 2 flux. Takahashi et al ., DSR I, 2009: 4.5 million data points. Takahashi et al ., DSR I, 2009: 3 million data points. Global CO 2 data coverage. - PowerPoint PPT PresentationTRANSCRIPT
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)