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Discussions about scope and goals of the WG

Discussions about scope and goals of the WG. Cédric Jamet Kick-off meeting Wimereux, France May, 14, 2014. Why a new IOCCG WG? . Complement of the IOCCG report #10: «   Atmospheric Correction for Remotely-Sensed Ocean-Colour Products » (Wang, 2010)

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Discussions about scope and goals of the WG

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  1. Discussions about scope and goals of the WG

    Cédric Jamet Kick-off meeting Wimereux, France May, 14, 2014
  2. Why a new IOCCG WG? Complement of the IOCCG report #10: «  Atmospheric Correction for Remotely-SensedOcean-ColourProducts » (Wang, 2010) Update (couldalsobe an update of IOCCG report #3) This WG focused mainly on open ocean waters And in coastal waters?? Need for guidances on using the alreadydeveloped AC  Purpose of this new WG
  3. For a sediment-dominated Case-2 water with typical maritime aerosols: all four operational algorithms produced slightly larger errors in the nLwin the blue bands, mainly due to an incorrect estimation of the NIR ocean contributions nLwin the longer visible wavelengths (e.g. 555 nm), and radiance band ratio values can be retrieved accurately. Since nLwspectra for the sediment-dominated waters highest in green-red λ: satellite-derived nLw and radiance ratio at the longer visible bands used for retrieval of sediment-dominated water opticaland biologicalproperties. For a yellow substance-dominated Case-2 water: all four operational algorithms performed poorly, particularly for nLwin the blue nLw in blue should beused to obtain CDOM absorption information (i.e., to distinguish it from phytoplankton absorption), even though the blue radiance is difficult to derive accurately Spectral shape of nLwratios, could be helpful for deriving the water property for yellow substance dominated waters. For absorbing aerosols: All four operational algorithms failed to produce accurate nLw spectra in visible λ Satellite derived nLw values significantly underestimated For aerosol retrievals: AOT data over oceans derived accurately using the vector aerosol LUT (errors within 5%. Ocean nLwspectra can be derived accurately using the scalar aerosol LUT
  4. Why a new IOCCG WG? Complement of the IOCCG report #10: «  Atmospheric Correction for Remotely-SensedOcean-ColourProducts » (Wang, 2010) Update (couldalsobe an update of IOCCG report #3) This WG focused mainly on open ocean waters And in coastal waters?? Need for guidances on using the alreadydeveloped AC  Purpose of this new WG
  5. Summary Goal: Inter-comparison and evaluation of existing AC algorithms over turbid/coastal waters  Understanding retrievals differences between algorithms Challenge: to understand the advantages and limitations of each algorithm and their performance under certain atmospheric and oceanic conditions Only focus on AC algorithms that deal with a non-zero NIR water-leaving radiances. High demand for AC guidelines Outputs timely  Guidances on the use of AC over turbid waters  Recommendations for improving and selecting the optimal AC Not a sensor-oriented exercise
  6. Questions How well do the aerosolsneed to beretrieved? Does the technique matter? How good is the extrapolation from SWIR to NIR to VIS? How to improve AC with the historicwavelengths? Better bio-opticalmodels New contrains (such as relationshipsbetweenRrs, Goyens et al. (2014)) Regional AC? Do wereallyneed extra wavelengths in NIR/SWIR? What info canoffer the future satellite sensors?
  7. Evaluation of AC Can round robin lead to improvements? What can we learn? Range of validity and advantages Limitations Sensitivity studies Fixed aerosols Variation/change of the bio-optical model Fixed bio-optical model  Variation/change of the aerosol models Uncertainties propagation and budget on the hypothesis Ruddick et al. (2000) Bayseian statistics for NN (Aires et al., 2004a, 2004b, 2004c) Uncertainties on the NN parameters (weights) Uncertainties on the outputs Others ?
  8. Evaluation of AC Can round robin lead to improvements? Whatcanwelearn? Drawbacks and advantages Limitations Sensitivitystudies Fixedaerosols Variation/change of the bio-optical model Fixed bio-optical model  Variation/change of the aerosolmodels Uncertainties propagation and budget on the hypothesis Ruddick et al. (2000) Neukermans et al., (2012) Bayseianstatistics for NN (Aires et al., 2004a, 2004b, 2004c) Uncertainties on the NN parameters (weights) Uncertainties on the outputs
  9. Evaluation of AC Can round robin lead to improvements? Whatcanwelearn? Drawbacks and advantages Limitations Sensitivitystudies Fixedaerosols Variation/change of the bio-optical model Fixed bio-optical model  Variation/change of the aerosolmodels Uncertainties propagation and budget on the hypothesis Ruddick et al. (2000) Neukermans et al., (2012) Bayseianstatistics for NN (Aires et al., 2004a, 2004b, 2004c) Uncertainties on the NN parameters (weights) Uncertainties on the outputs
  10. Whichsensors SeaWiFS MODIS-AQUA MERIS VIIRS GOCI ????
  11. Whichsensors SeaWiFS MODIS-AQUA for starting MERIS VIIRS GOCI ????
  12. Whichsensors SeaWiFS MODIS-AQUA for starting MERIS after VIIRS GOCI ????
  13. Which algorithms? many approaches exist, here are a few examples: assign aerosols () and/or water contributions (Rrs(NIR)) e.g., Hu et al. 2000, Ruddick et al. 2000 use shortwave infrared bands e.g., Wang & Shi 2007 correct/model the non-negligible Rrs(NIR) Lavender et al. 2005 MERIS Bailey et al. 2010 used in SeaWiFS Reprocessing 2010 Shanmugam, 2012 any sensor Wang et al. 2012 GOCI use a coupled ocean-atmosphere optimization e.g., Moore et al. (1999); Chomko & Gordon 2001, Stamnes et al. 2003, Jamet et al., 2005, Brajard et al., 2006a, b, 2008, 2012; Ahn and Shanmugam, 2007; Kuchinke et al. 2009; Steinmetz et al., 2010; Other e.g., Chen et al., 2014; Doerrfer et al., (2007); He et al., 2013; Mao et al., 2013, 2014; Schroeder et al. (2007); Shanmugam and Tholkapiyan, 2014; Singh and Shanmugam, 2014
  14. Which algorithms? many approaches exist, here are a few examples: assign aerosols () and/or water contributions (Rrs(NIR)) e.g., Hu et al. 2000, Ruddick et al. 2000 use shortwave infrared bands e.g., Wang & Shi 2007 correct/model the non-negligible Rrs(NIR) Lavender et al. 2005 MERIS Bailey et al. 2010 used in SeaWiFS Reprocessing 2010 Shanmugam, 2012 any sensor Wang et al. 2012 GOCI use a coupled ocean-atmosphere optimization e.g., Moore et al. (1999); Chomko & Gordon 2001, Stamnes et al. 2003, Jamet et al., 2005, Brajard et al., 2006a, b, 2008, 2012; Ahn and Shanmugam, 2007; Kuchinke et al. 2009; Steinmetz et al., 2010; Other e.g., Chen et al., 2014; Doerrfer et al., (2007); He et al., 2013; Mao et al., 2013, 2014; Schroeder et al. (2007); Shanmugam and Tholkapiyan, 2014; Singh and Shanmugam, 2014
  15. Which algorithms? All published/available atmospheric correction algorithms? Selected only few depending on their hypothesis: (Hu et al. (2000) ~= Ruddick et al. (2000), is it necessary to take both? Send datasets to developers and send their results back? Every algorithm (when possible) implemented in SeaDAS so the entire processing chain is similar (differences in results only from AC)  Is it possible/reasonable?
  16. Which algorithms? All published/available atmospheric correction algorithms? YES, WHEN POSSIBLE Selected only few depending on their hypothesis: (Hu et al. (2000) ~= Ruddick et al. (2000), is it necessary to take both? Email to developers to ask their participation to share their algorithms: natural selection? Send datasets to developers and send their results back? YES Every algorithm (when possible) implemented in SeaDAS so the entire processing chain is similar (differences in results only from AC)  Is it possible/reasonable? ACTION TO SEAN BAILEY for SeaDAS and C. Brockmann for BEAM (C. Jamet)
  17. Which parameters? Remote-Sensing reflectance (output of SeaDAS): Rrs Normalized water-leaving reflectance: nρw Normalized water-leaving radiance: nLw Water-leaving radiance: Lw Water Radiance-Luminance: RLw Do all algorithms take the same definition?
  18. Which parameters? Remote-Sensing reflectance (output of SeaDAS): Rrs Normalized water-leaving reflectance: nρw Normalized water-leaving radiance: nLw Water-leaving radiance: Lw Water Radiance-Luminance: RLw Do all algorithms take the same definition?  ACTION: Table with all the possible AC algorithms with inputs and outputs (C. Jamet)
  19. Datasets (1/2) Classic match-upsanalysis: Which in-situ datasets: AERONET-OC: moderatelyturbid waters LOG/MUMM TriOS: moderately to veryturbid waters ASD measurements for VITO? NOMAD, SeaBASS? Data in estuaries? Other? Need for high-quality NIR nLwmeasurements
  20. Datasets (1/2) Classic match-upsanalysis: Which in-situ datasets: AERONET-OC: moderatelyturbid waters LOG/MUMM TriOS: moderately to veryturbid waters ASD measurements for VITO NOMAD, SeaBASSfrom NASA DATA from CSIRO DATA from X. He DATA from P. Shanmugam ACTION: Ask PI of MERMAID in-situ data to sharewith WG ACTION TO K. Ruddick for hisdatasets (C. Jamet) Needfor high-quality NIR nLwmeasurements COMPARISON OF NIR(nLw)
  21. Datasets (1/2) Whatis a match-up? Bailey and Werdell (2006) Δt= +/- 2h? Spatial homogeneitycriteria: std/mean on nLw or on tau? Spatial homogeneitycriteria: valid if <0.15 or 0.20? 3x3 pixels box? All valid pixels or a certain number (>5 or 6)?
  22. Datasets (2/2) Image analysis over selected areas: French Guiana, Eastern English Channel/NorthSea, Vietnam, Yangtzecoasts, Amazon river???? Comparison of aerosolproperties and nLw patterns Transectsfromcoasts to case-1 waters
  23. Datasets (2/2) Image analysis over selected areas: French Guiana, Eastern English Channel/NorthSea, Vietnam, Yangtzecoasts, Amazon river???? Each participant provides info about theirregions of expertise to C. Jamet Careful attention to sensor saturation: NOT AN ISSUE FOR THIS WG Comparison of aerosolproperties and nLwpatterns YES Transectsfromcoasts to case-1 waters  YES
  24. Inter-comparison (1/3) Optical water type: Classification of nLw as a function of IOPs, contents Sensitivitiesstudies Moore et al. (2009), Vantrepotte et al. (2012) Necessity to validate NIR nLw Only validation of visible nLw BUT goal of AC is to removeatmospherefrom NIR bands (most of the time) Otherway to validate Determinationaerosolopticalproperties Use of AOP to estimatepathreflectance via RTE Reconstruction of Lrcusing Lw + reconstructedLpath Comparison of reconstructedLrc to measuredLrc
  25. METHODS Classification of Lw spectra per water type - 4 water type classes defined by Vantrepotte et al. (2012) - Novelty detection technique: Assigns each spectra to one of the 4 water type classes using the Mahalanobis distance Distinguish classes based on normalized reflectance spectra Focus on turbid waters only ! D'Alimonte et al. (2003)
  26. Inter-comparison (2/3) Optical water type: Classification of nLw as a function of IOPs, contents Sensitivitiesstudies Moore et al. (2011), Vantrepotte et al. (2012) Necessity to validate NIR nLw Only validation of visible nLw BUT goal of AC is to removeatmospherefrom NIR bands (most of the time) Otherway to validate Determinationaerosolopticalproperties Use of AOP to estimatepathreflectance via RTE Reconstruction of Lrcusing Lw + reconstructedLpath Comparison of reconstructedLrc to measuredLrc
  27. Inter-comparison (3/4) Impact of observation angles: Are AC sensitive to some observation angles? CCI round-robin: YES How do we do that? Images and/or sensitivitystudies? Sensitivitiesstudies: Need for simulateddatasets: Atmospheric RTE: Stamnes et al.; He et al.; other? Whichaerosolmodels? Shettle and Fenn, AERONET-like, ot Bio-optical model: Hydrolight How to fix the IOPs/oceanicconstituents  COASTCOLOUR + IOCCG round robin Fixedaerosol/varyingIOPs Varyingaerosols/fixedIOPs What do wesimulate: L(TOA) or just L(rc)? If L(TOA), how do wesimulateLr, Lwc, Lg??
  28. Inter-comparison (3/4) Impact of observation angles: Are AC sensitive to some observation angles? CCI round-robin: YES How do we do that? Images and/or sensitivitystudies? Sensitivitiesstudies: Need for simulateddatasets: Atmospheric RTE: Stamnes et al.; He et al.; other? Whichaerosolmodels? Shettle and Fenn, AERONET-like, ot Bio-optical model: Hydrolight How to fix the IOPs/oceanicconstituents  COASTCOLOUR + IOCCG round robin Fixedaerosol/varyingIOPs Varyingaerosols/fixedIOPs What do wesimulate: L(TOA) or just L(rc)? If L(TOA), how do wesimulateLr, Lwc, Lg?? ACTION: Definition of a set of few cases as benchmark to validate FUB RTM, C-VDISORT and PCOART (K. Stamnes, T. Schroeder and X. He) Choice of the RTM TIMELINE: beforenextOceanOptics Generation of atmosphere and oceanLUTs: before end of the year
  29. Inter-comparison (3/4) Impact of observation angles: Are AC sensitive to some observation angles? CCI round-robin: YES How do we do that? Images and/or sensitivitystudies? Sensitivitiesstudies: Need for simulateddatasets: Atmospheric RTE: Stamnes et al.; He et al.; other? Whichaerosolmodels? Shettle and Fenn, AERONET-like, ot Bio-optical model: Hydrolight How to fix the IOPs/oceanicconstituents  COASTCOLOUR + IOCCG round robin Fixedaerosol/varyingIOPs Varyingaerosols/fixedIOPs What do wesimulate: L(TOA) or just L(rc)? If L(TOA), how do wesimulateLr, Lwc, Lg?? Simulation of L(TOA) AND L(rc) with La, Lra, Lw and associated transmittances (L and ρ)
  30. Inter-comparison (4/4) Time series over selectedregions Correlationbtaerosols, IOPs, Rrs, …. Definition of objective criteria for comparison: Need for metrics Validation of aerosolopticalproperties Do wewantaccurate AOP of justaccurateLpath? Is it important? What info doesitgive us on the accuracy of AC? Vicariouscalibration
  31. Inter-comparison (4/4) Time series over selectedregions Correlationbtaerosols, IOPs, Rrs, …. Definition of objective criteria for comparison: Need for metric Whichstatisticalparameters: RMSE RELATIVE ERROR Slope Coefficient correlation Bias ACTION TO DAGMAR MULLER FOR EXPERIENCE FROM CCI (C. Jamet) Validation of aerosolopticalproperties Do wewantaccurate AOP of justaccurateLpath? Is it important? What info doesitgive us on the accuracy of AC? Vicariouscalibration
  32. Inter-comparison (4/4) Time series over selectedregions Correlationbtaerosols, IOPs, Rrs, …. Definition of objective criteria for comparison: Need for metrics? (CCI) Is itnecessary? Validation of aerosolopticalproperties Do wewantaccurate AOP of justaccurateLpath? Is it important? What info doesitgive us on the accuracy of AC? Vicariouscalibration Keep in mind ACTION to S. Bailey for more inputs and possibility of vicariouscalibratedevery AC algorithm
  33. What next October 2014: OceanOpticsconference: possibility to book a meeting space 6 monthprogress Whocan attend? 2015: Development/gatheringsyntheticaldatasets Match-ups and transectanalysis 2016: Match-ups and transectanalysis Sensitivityanalysisusingsyntheticaldatasets
  34. Whatnext October 2014: OceanOpticsconference: possibility to book a meeting space 6 monthprogress Results of RTM comparison Collection of in-situ datasets Choice of AC algorithms Tables on AC algorithms (inputs, outputs) Choice of regions of interest 2015: Development/gatheringsyntheticaldatasets Match-ups and transectanalysis 2016: Match-ups and transectanalysis Sensitivityanalysisusingsyntheticaldatasets
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