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The sensors studied

Merging of ocean color data from multiple satellite missions C. Pottier 1,2 , V. Garçon 1 , A. Turiel 3 , G. Larnicol 2 , J. Sudre 1 , P.Y. Le Traon 4 , P. Schaeffer 2 1 : LEGOS – 2 : CLS – 3 : ICM – 4 : IFREMER. The sensors studied.

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The sensors studied

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  1. Merging of ocean color datafrom multiple satellite missionsC. Pottier1,2, V. Garçon1, A. Turiel3, G. Larnicol2, J. Sudre1, P.Y. Le Traon4 , P. Schaeffer2 1 : LEGOS – 2 : CLS – 3 : ICM – 4 : IFREMER The sensors studied Globcolour 1st User Consultation Meeting, Villefranche sur Mer, December 4-6, 2006

  2. –Globcolour 1st User Consultation Meeting – Methods and zone of interest – 1 1 1 2 3 2 50 65 50 11 50 4 51 52 15 19 5 54 54 53 16 18 69 66 6 17 56 60 7 34 33 35 12 64 67 36 61 8 63 14 13 30 62 9 72 70 64 59 32 31 10 20 71 22 37 80 80 80 68 58 81 21 81 82 82 83 83 83 Methods and zone of interest • Error weighted-averaging • Objective analysis • Global application for 2003 • Wavelets (ongoing work) => Gulf Stream area Biogeochemical provinces [Longhurst, 1998]

  3. SeaWiFS: 2410 matchups • YEAR 2003 • AMT 12 and AMT 13 (Atlantic Meridional Transect, UK) • SeaBASS (SeaWiFS Bio-optical And Storage System, USA) • National Oceanographic Data Center (USA) • International Council for the Exploitation of the Sea • National Institute of Oceanography (India) • OISO • MINERVE 0203-R2, 0204-R4, 0304-R0, and 0304-R1 • ARGAU3 • DIAPAZON 7, 8, and 9 • DYFAMED • Other cruises (Yves Dandonneau, pers. com.) MODIS/Aqua: 2789 matchups

  4. SeaWiFS’ error measurement MODIS/Aqua’s error measurement % of chlorophyll % of chlorophyll

  5. SeaWiFS’ bias MODIS/Aqua’s bias % of chlorophyll % of chlorophyll

  6. Error-weighted averaging Objective analysis in Pottier et al., IEEE TGRS, 2006

  7. – Globcolour 1st User Consultation Meeting - Error-weighted-averaging – Error-weighted averaging[Pottier et al., IEEE TGRS, 2006][Gregg et al., IOCCG Report, 2006] • Input parameters for each sensor: • Map of chlorophyll for the ith day • Map of spatial errors (according to matchups) • Computation made on logtransformed values • Output products: • Map of combined chlorophyll for the ith day • Map of associated errors

  8. SeaWiFS Combined data MODIS/Aqua Chlorophyll-a concentration (mg/m^3) Error Spatial repartition of the data % of chlorophyll 03/26/2003

  9. – Globcolour 1st User Consultation Meeting– Objective analysis – Objective analysis[Pottier et al., IEEE TGRS, 2006][Gregg et al., IOCCG Report, 2006] • Aim: to determine the value of a field  at a point in space and time, given various measurements of the field unevenly spread over time and space obsi (i=1…n) • Best least squares linear estimator est(x) (Bretherton et al., 1976): • A priori knowledge of: • The covariance function (i.e. variance + correlation function) • The measurement noise and the bias (obtained from the matchups)

  10. SeaWiFS Combined data MODIS/Aqua Chlorophyll-a concentration (mg/m^3) Error Spatial repartition of the data % of chlorophyll 03/26/2003

  11. Wavelets Use of multi-resolution algorithm to compute the wavelet coefficients « h »: convolution with a low-pass filter « g »: convolution with a high-pass filter « 2 »: keep 1 row (or col.) on 2

  12. – Globcolour 1st User Consultation Meeting– Wavelets – Wavelets [Pottier, Turiel and Garçon]1st step: estimation of the missing data Vertical details

  13. – Globcolour 1st User Consultation Meeting– Wavelets – Wavelets [Pottier, Turiel and Garçon]2nd step: combination

  14. SeaWiFS MODIS/Aqua Original image (1/12°) Original image (1/24°) 03/26/2003 Reconstructed image Reconstructed image Weighted averaging (1/12°) Wavelets (1/24°) Objective analysis (1/12°)

  15. – Globcolour 1st User Consultation Meeting - Ongoing work – Ongoing work • Weighted averaging and objective analysis • Fully operational for near real time at the global scale • Statistics computation needed for all time series • Addition of other sensors (MERIS…) • Wavelets: very promising ! But still a lot of work to do !

  16. Oceanographic application:using combined SeaWiFS and MODIS/Aqua ocean color data • Southern ocean (35°S – 50°S) • What are the dominant modes of variability in sea level anomalies and surface chlorophyll concentrations in this circumpolar belt ? (Pottier et al., 2004; Pottier et al., 2006)

  17. 2002-2006 period : 3/0 mode of variability Band 35°S-45°S Weekly sea level anomalies Monthly SeaWiFS chlorophyll Weekly combined chlorophyll SeaWiFS + MODIS/Aqua Band 45°S-50°S

  18. Multi-resolution wavelets algorithm

  19. – Globcolour 1st User Consultation Meeting– In conclusion – In conclusion : • Within MERSEA,

  20. – Globcolour 1st User Consultation Meeting– Wavelets – Error

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