1 / 30

Schroeder T, Lovell J , Clementson L, King E, Brando V

Evaluation of MODIS chlorophyll algorithms in Australian continental shelf waters: The IMOS match-up data base. Schroeder T, Lovell J , Clementson L, King E, Brando V. 9 July 2014 Australian Marine Science Association Conference, Canberra , Australia. CSIRO Oceans and Atmosphere Flagship.

dana
Download Presentation

Schroeder T, Lovell J , Clementson L, King E, Brando V

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Evaluation of MODIS chlorophyll algorithms in Australian continental shelf waters:The IMOS match-up data base Schroeder T, Lovell J, Clementson L, King E, Brando V 9 July 2014 Australian Marine Science Association Conference, Canberra, Australia CSIRO Oceans and Atmosphere Flagship

  2. Motivation • No consistent national validation approach CSIRO Oceans and Atmosphere Flagship

  3. Motivation • No coherent algorithm validation on continental scale • Global algorithms are biased towards northern hemisphere data CSIRO Oceans and Atmosphere Flagship

  4. The Australian “bio-optical data desert” CSIRO Oceans and Atmosphere Flagship

  5. Motivation • No coherent algorithm validation on continental scale • Global algorithms are biased towards northern hemisphere data • IMOS Ocean Colour Sub-facility is addressing data gap • Compilation of a national bio-optical data base CSIRO Oceans and Atmosphere Flagship

  6. IMOS data updates to NASA SeaBASS(since Jan 2014) http://seabass.gsfc.nasa.gov/wiki

  7. In-situ HPLC chlorophyll – IMOS data base N=1992 http://imos.aodn.org.au/webportal/ CSIRO Oceans and Atmosphere Flagship

  8. Motivation • No coherent algorithm validation on continental scale • Global algorithms are biased towards northern hemisphere data • IMOS Ocean Colour Sub-facility is addressing data gap • Compilation of a national bio-optical data base • Production and provision of Ocean Colour data CSIRO Oceans and Atmosphere Flagship

  9. L2 re-mapped swath https://rs.nci.org.au/u83/public/data/modis/l2.oc.70/aqua/ L2 continental scale mosaics http://thredds0.nci.org.au/thredds/catalog/u83/modis/oc.mosaics.70/catalog.html In future also via http://imos.aodn.org.au/webportal/

  10. Motivation • No coherent algorithm validation on continental scale • Global algorithms are biased towards northern hemisphere data • IMOS Ocean Colour Sub-facility is addressing data gap • Compilation of a national bio-optical data base • Production and provision of Ocean Colour data • Evaluation of algorithm accuracy: • Combining coincident in-situ chlorophyll and remote sensing measurements CSIRO Oceans and Atmosphere Flagship

  11. Which chlorophyll product to choose?IMOS MODIS-A repository based on SeaDAS v7.0 processing CSIRO Oceans and Atmosphere Flagship Empirical algorithms OC3 (MODIS standard algorithm) Clark Semi-analytical algorithms GSM (Garver-Siegel-Maritorena model) Carder

  12. IMOS in-situ HPLC data coverageTime constrain to satellite overpasses ±1 day All HPLC data (N=1992) ±1 day (N=262) CSIRO Oceans and Atmosphere Flagship

  13. IMOS in-situ HPLC data coverageTime constrain to satellite overpasses ±2 hours All HPLC data (N=1992) ±1 day (N=262) ±2 hours (N=34) CSIRO Oceans and Atmosphere Flagship

  14. Data distribution NOMAD vs IMOS CSIRO Oceans and Atmosphere Flagship

  15. Match-up Methodology CSIRO Oceans and Atmosphere Flagship • For each in-situ Chl-a data from IMOS data base identify matching satellite images within ±2 hours upto ±1 day • Extract satellite derived CHL observations at in-situ locations within a 5 km radius for open ocean waters, 3 km for coastal waters, calculate median and standard deviation • Apply quality control flags • Land, cloud, glint, Sun zenith < 60, view zenith < 60, ... • Calculate statistics (RMSE, %-error, bias) of match-up pairs • Classify match-up pairs according to Optical Water Type (OWT) • 8 classes (Moore et al. 2009) • Extra class for cocolithophore bloom

  16. Optical Water Type (OWT) classificationMoore et al. 2009 CSIRO Oceans and Atmosphere Flagship

  17. OC3 Satellite CHL (MODIS-A) In-situ CHL CSIRO Oceans and Atmosphere Flagship

  18. OC3 Satellite CHL (MODIS-A) In-situ CHL CSIRO Oceans and Atmosphere Flagship

  19. OC3 Satellite CHL (MODIS-A) In-situ CHL CSIRO Oceans and Atmosphere Flagship

  20. OC3 Satellite CHL (MODIS-A) In-situ CHL CSIRO Oceans and Atmosphere Flagship

  21. OC3 Satellite CHL (MODIS-A) In-situ CHL CSIRO Oceans and Atmosphere Flagship

  22. OC3 Satellite CHL (MODIS-A) In-situ CHL CSIRO Oceans and Atmosphere Flagship

  23. OC3 Satellite CHL (MODIS-A) In-situ CHL CSIRO Oceans and Atmosphere Flagship

  24. CSIRO Oceans and Atmosphere Flagship

  25. CSIRO Oceans and Atmosphere Flagship

  26. N=264 N=60 ±3 h ±1 day CSIRO Oceans and Atmosphere Flagship

  27. Match-up Statistics ±1 Day ±3 hr CSIRO Oceans and Atmosphere Flagship

  28. Conclusions • IMOS OC sub-facility provides a useful platform for nationally consistent evaluation of ocean colour products • All data freely available through the IMOS portal • Ongoing effort (currently secured until 06/2015) • Optical Water Types vital to constrain match-up analysis – exclude out-of-range conditions – larger deviations OWT 7,8,9 • In-situ HPLC does not confirm presence of cocolithophore (OWT9) • Reducing time window for match-ups improves statistics (except Carder) • Empirical algorithms perform better than semi-analytical Performance ranking: OC3, Clark, Carder, GSM CSIRO Oceans and Atmosphere Flagship

  29. The IMOS bio-optical data base needs your data! It is a community effort.

  30. Thank you – question? Dr Thomas Schroeder CSIRO Oceans and Atmosphere Flagship, Brisbane Thomas.Schroeder@csiro.au Acknowledgements: SeaDAS Development Group and the OPBG at NASA GSFC for development, support and distribution of the SeaDAS software CSIRO Oceans and Atmosphere Flagship

More Related