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New Fluorescence Algorithms for the MERIS Sensor

New Fluorescence Algorithms for the MERIS Sensor. Yannick Huot and Marcel Babin Laboratoire d’Oc éanographie de Villefranche Antoine Mangin and Odile Fanton d'Andon ACRI-ST 28 September 2005. Research funded by:

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New Fluorescence Algorithms for the MERIS Sensor

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  1. New Fluorescence Algorithms for the MERIS Sensor Yannick Huot and Marcel Babin Laboratoire d’Océanographie de Villefranche Antoine Mangin and Odile Fanton d'Andon ACRI-ST 28 September 2005 Research funded by: A fellowship from the NaturalSciencesandEngineeringResearchCouncil (NSERC)

  2. What is fluorescence andwhy would one care?

  3. Phytoplankton fluorescence Fluorescence volume flux Quantum yield of fluorescence Chlorophyll concentration Chlorophyll specific absorption Reabsorption parameter Scalar Irradiance • Just outside the cells:

  4. Two products of interest The Biomass Index of physiological status May be useful in regions where the chlorophyll concentration cannot be obtained with standard ocean colour algorithms Processes studies in case 1 waters Today we are developing algorithms for these two products applicable to case 1 waters

  5. Measurement optics Subsurface upwelling radiance due to fluorescence Attenuation of downwelling and upwelling light Terms from previous page Geometrical factor

  6. Adapting recently published MODIS algorithms to MERIS

  7. The two products Fixed quantum yield Measured chlorophyll concentration

  8. Concept of the algorithm • Satellite algorithms: • : MERIS PAR • Chl: MERIS case 1, blue to green ratio algorithm • Luf(0-): Transform from w to Lu and baseline method • Kd(490): “Improved” blue to green ratio algorithm • Case 1 waters relationships functions of Kd(490) • versus measured Kd(490); • Bricaud et al. 1998 statistics, vs. chl • Morel et al. 2001, Kd(490) vs.chl

  9. WARNING:For today’s presentationsome approximations are made that would not be necessary in standard algorithms.

  10. Scalar irradiance • MERIS product gives Ed(0-,PAR) • For fluorescence we want • We assumed: 1) Upwelling irradiance negligible 2) d(0-) = 0.75 for the whole scene We thus use:

  11. Concept of the algorithm • Satellite algorithms: • : MERIS PAR • Chl: MERIS case 1, blue to green ratio algorithm • Luf(0-): Transform from w to Lu and baseline method • Kd(490): “Improved” blue to green ratio algorithm • Case 1 waters relationships functions of Kd(490) • versus measured Kd(490); • Bricaud et al. 1998 statistics, vs. chl • Morel et al. 2001, Kd(490) vs.chl

  12. Going from w to Lu First step to Lw(0+) Atmospheric transmission (td) has to be approximated when one doesn’t have access to the processing chain intermediate products (probably a small error) Second step to Lu(0-) • Problem: MERIS algorithm returns w: to calculate a quantum yield we need Lu(0-):

  13. The baseline method • MERIS bands dedicated to the natural fluorescence measurements are: • 665, 681, and 709 nm (bands 7, 8, 9) This approximation is good in case 1 waters (Huot et al. 2005) but great care must be taken in case 2 waters (see next talk by Babin and Huot)

  14. Concept of the algorithm • Satellite algorithms: • : MERIS PAR • Chl: MERIS case 1, blue to green ratio algorithm • Luf(0-): Transform from w to Lu and baseline method • Kd(490): “Improved” blue to green ratio algorithm • Case 1 waters relationships functions of Kd(490) • versus measured Kd(490); • Bricaud et al. 1998 statistics, vs. chl • Morel et al. 2001, Kd(490) vs.chl

  15. Kd490: A “MERIS” algorithm NOMAD dataset: see Werdell, P.J. and S.W. Bailey, 2005: An improved bio-optical data set for ocean color algorithm development and satellite data product validation. Remote Sensing of Environment , 98(1), 122-140. Thank you to all contributors… See also: http://oceancolor.gsfc.nasa.gov/REPROCESSING/Aqua/R1.1/

  16. Checking the Kd(490) algorithm Best fit polynomial Morel and Maritorena 2001 -The two algorithms are consistent, with some bias at high chl -Waters examined do not depart strongly from case 1 relationships

  17. Concept of the algorithm • Satellite algorithms: • : MERIS PAR • Chl: MERIS case 1, blue to green ratio algorithm • Luf(0-): Transform from w to Lu and baseline method • Kd(490): “Improved” blue to green ratio algorithm • Case 1 waters relationships functions of Kd(490) • versus measured Kd(490); • Bricaud et al. 1998 statistics, vs. chl • Morel et al. 2001, Kd(490) vs.chl

  18. Case 1 water relationships Bricaud, A., H. Claustre, J. Ras, and K. Oubelkheir. 2004. Journal of Geophysical Research 109: C11010,doi:11010.11029/12004JC002419. Morel, A., and S. Maritorena. 2001. Journal of Geophysical Research 106: 7163-7180. A little algebra: A little more algebra: Some calculus and a numerical model:

  19. Let’s apply it on an image now…

  20. Noise in the 681nm band Scene from the Benguela upwelling region measured on July 14, 2003, Second reprocessing.

  21. Measured by MERIS

  22. Chlorophyll algorithm Best fit 1:1 line

  23. Chlorophyll algorithm map

  24. Quantum yield algorithm

  25. Quantum yield algorithm

  26. Comparison with MODIS: f MODIS MERIS -Very noisy -Hard to use presently -However, much of the noise is not random and it may be possible to correct for it - Quantum yield too high?

  27. Are we measuring something real? No clear reason for this trend Consistent with non-photochemical quenching

  28. Are we measuring something real? Answer: Perhaps, but what?

  29. Conclusion • We proposed two algorithms for MERIS fluorescence bands • One for chlorophyll • One for the quantum yield • MERIS band at 681 nm is more noisy than the 665 and 709 bands • Algorithms need to be fully validated but preliminary results are encouraging Future prospects • We hope to implement the algorithms with intermediate products of the processing chain to avoid the limitations of the level two products. • We are testing iterative fluorescence algorithms using only the fluorescence bands for the retrieval of chlorophyll.

  30. Future prospects: first glimpse Today’s algorithm Fluorescence bands only FLH It’s potential will depend on our ability to reduce the noise observed in the 681 nm channel

  31. Thanks to • David Antoine • Norman Fomferra • André Morel

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