Presentation is loading. Please wait.

Presentation is loading. Please wait.

REMOTE SENSING OF SOUTHERN OCEAN AIR-SEA CO 2 FLUXES A.J. Vander Woude Pete Strutton and Burke Hales.

Similar presentations


Presentation on theme: "REMOTE SENSING OF SOUTHERN OCEAN AIR-SEA CO 2 FLUXES A.J. Vander Woude Pete Strutton and Burke Hales."— Presentation transcript:

1 REMOTE SENSING OF SOUTHERN OCEAN AIR-SEA CO 2 FLUXES A.J. Vander Woude Pete Strutton and Burke Hales

2 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

3 Global CO 2 data coverage

4 Southern Ocean & atmospheric CO 2 Observations versus models Gruber et al. 2009

5 In some places there are no observations: pCO 2 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 (~10 2 to 10 3 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?

6 Steps to Create Predictive Satellite Algorithms: West Coast Example

7 Remote Sensing Climatology Monthly Data Chlorophyll a (mg/m 3 ) Wind speed (m/s) Sea Surface Height (cm) OI Reynolds Sea Surface Temperature (°C) Sea Surface Height: AVISO Multimission Chlorophyll: SeaWiFS , MODIS/Aqua + SeaWiFS Merged , MODIS/Aqua Wind speed: QuickSCAT OI Reynolds SST: AVHRR , AVHRR+AMSR

8 Steps to Create Predictive Satellite Algorithms

9 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

10 Overview of Predictive Satellite Algorithms A Alkalinity and DIC from the McNeil climatologies Optimizing: Alk, DIC, T i, Heating/Mixing term, T cr Chlorophyll term Each has a constant, longitude, latitude & seasonal signal Powell’s Optimization

11 pCO 2 Results & Accuracy of Regional Model SummerSpring AutumnWinter pCO 2 (ppm) Obo Observed Predicted Region 4 May and June Red is a source to the atmosphere White is at atmospheric Blue is a sink, into the ocean

12 Conclusions and future work Satellite algorithms offer a way to fill gaps and better quantify spatial and temporal variability of CO 2 Next: -- Finishing the monthly algorithms, by region as well as Seasonal and interannual variability and produce maps of CO 2 fluxes for the Southern Ocean -- More rigorous comparison with climatologies and models.

13 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

14 CDIAC in situ pCO 2 Coverage 1.4 million data points in the Southern Ocean, south of 40° S

15 SO GasEx observations and satellite predictions

16 SO GasEx observations and McNeil predictions

17 SO GasEx observations and Takahashi predictions

18 Southern Ocean & atmospheric CO 2 Gruber et al Contemporary sink of:.1 to.5 PgC/yr (circulation models & atm and oceanic inversion models).5 to.7 PgC/yr (pCO 2 measurements, Takahashi et al. 2002).15 to.65 PgC/yr (empirical estimated pCO 2, McNeil et al., 2007)


Download ppt "REMOTE SENSING OF SOUTHERN OCEAN AIR-SEA CO 2 FLUXES A.J. Vander Woude Pete Strutton and Burke Hales."

Similar presentations


Ads by Google