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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.

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

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  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

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