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LMD, Paris, October 5, 2007

Optimal Retrieval of Vegetation Canopy Characteristics Using Operational MODIS and MISR Surface Albedo Products. Bernard Pinty , T. Lavergne, T. Kaminski, O. Aussedat, N. Gobron and M. Taberner with contributions from R. Giering, M. M. Verstraete, M. Vossbeck and J-L. Widlowski

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LMD, Paris, October 5, 2007

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  1. Optimal Retrieval of Vegetation Canopy Characteristics Using Operational MODIS and MISR Surface Albedo Products Bernard Pinty, T. Lavergne, T. Kaminski, O. Aussedat, N. Gobron and M. Taberner with contributions from R. Giering, M. M. Verstraete, M. Vossbeck and J-L. Widlowski EC-JRC Institute for Environment and Sustainability, Ispra, Italy FastOpt, Hamburg, Germany JRC – Ispra LMD, Paris, October 5, 2007

  2. Complex land-surface RT effects on short term climate: the snow case with ECMWF/NCEP Ref: Viterbo and Betts, 1999, JGR “…weather forecasts significantly underestimated air temperatures over boreal, sometimes by as much as 10-15 C…” Ref: http://eobglossary.gsfc.nasa.gov/

  3. Complex land-surface RT effects on short term climate: the snow case with ECMWF/NCEP “…—the BOREAS team found that the models were overestimating albedo (the amount of light reflected by the surface). …” Ref: Viterbo and Betts, 1999, JGR Ref: http://eobglossary.gsfc.nasa.gov/

  4. How does radiation redistribute energy between the atmosphere and the biosphere? Scattered Fluxes by the surface Absorbed Fluxes in Vegetation Absorbed Fluxes in Soil

  5. What do we measure at global scale that we should model as well? Albedo of the surface in the VIS and NIR (MODIS and MISR) Absorbed Flux by green Vegetation in the VIS (FAPAR)

  6. VIS VIS+NIR How do we model the absorbed fluxes in vegetation and soil ? Correct partitioning between the flux that is absorbed : 1- in the vegetation layer 2- in the background Assessment of the fraction of solar radiant flux that is scattered (albedo) by, transmitted through and absorbed in the vegetation layer Pinty etal., (2006): Journal of Geophysical Research, doi:10.1029/2005JD005952

  7. What are the needs? • Update/improve the current Land Surface schemes describing the radiation transfer processes in vegetation canopies see 2-stream model by Pinty et al. JGR (2006).

  8. Requirements from a 2-stream model • 3 (effective) state variables: • Optical depth: LAI • single scattering albedo : Leaf reflectance+ Leaf transmittance 3. asymmetry of the phase function Leaf reflectance/transmittance • 2 boundary conditions: • Top:Direct and Diffuse atmospheric fluxes (known) • Bottom :Flux from background Albedo (unknown) Pinty etal., (2006): Journal of Geophysical Research, doi:10.1029/2005JD005952

  9. The concept of effective LAI Effects induced by internal variability of LAI

  10. Structure factor The concept of effective LAI

  11. What are the needs? • Update/improve the current Land Surface schemes describing the radiation transfer processes in vegetation canopies see 2-stream model by Pinty et al. JGR (2006). • Prepare for the ingestion/assimilation of RS flux products into Land Surface schemes Retrieve 2-stream model parameters from RS flux products

  12. Retrievals of model Parameters for Land surface schemes The inverse problem can be formulated in order to find solutions optimizing all the available information i.e., inferring statistically the state of the system Towards an integrated system for the optimal use of remote sensing flux products

  13. Re-analysis generating consistent dataset Posterior model parameters + uncertainties JRC-Two-stream Inversion Package: JRC-TIP Ancillary information, e.g. occurrence of snow and water RS flux products from various sources + uncertainties Prior knowledge on model parameters + uncertainties Radiation transfer model Time-independent operating mode JRC-TIP Diagnostic fluxes + uncertainties

  14. RS Flux products, e.g., Albedo Vis/NIR and/or FAPAR noted • Updated/benchmarked 2-stream model from Pinty • et al. JGR (2006) noted • A priori knowldege/guess on model parameters • noted uncertainty on the RS products is specified in the measurement set covariance matrix uncertainty associated the model parameter is specified via a covariance matrix INPUTS : prior knowledge

  15. Model parameters Parameter knowledge 2-stream model measurements Uncertainty measurements Uncertainty parameters • Computer optimized Adjoint and Hessian model of cost function from automatic differentiation technique • Assume Gaussian theory • Posterior uncertainties on retrieved parameters are estimated from the curvature of The core of the JRC-TIP Pinty etal., (2007): Journal of Geophysical Research, in press

  16. OUTPUTS: posterior knowledge • PDFs of all 2-stream model parameters: a posteriori uncertainty covariance matrix • Assessement of all fluxes predicted by the 2-stream model and their associated uncertainty: Pinty etal., (2007): Journal of Geophysical Research, in press

  17. Application results against model-based standard scenarios

  18. a priori knowledge on model parameters Pinty etal., (2007): Journal of Geophysical Research, in press

  19. Application results against model-based standard scenarios Application with measurements set d including various combinations of visible and near-infrared broadband radiant fluxes, i. e., Albedo (R), Transmission (T) and Absorption (A) PDFs for 7 model parameters to be estimated: LAI, Leaf and background properties in the two spectral domains

  20. VISIBLE NEAR-INFRARED measurement sets d Asymmetry phase function Asymmetry phase function Single scattering albedo Background albedo Single scattering albedo Background albedo a posteriori 1D Gaussian statistics @ 1σ Lavergne etal., (2007): EUR 22467 EN

  21. VISIBLE NEAR-INFRARED measurement sets d Asymmetry phase function Asymmetry phase function Single scattering albedo Background albedo Single scattering albedo Background albedo a posteriori 1D Gaussian statistics @ 1σ Lavergne etal., (2007): EUR 22467 EN

  22. a posteriori 2D Gaussian statistics @ 1.5σ Lavergne etal., (2007): EUR 22467 EN

  23. Results for scenarios built from Monte Carlo sampling of the a priori knowledge on model parameterstogether Pinty etal., (2007): Journal of Geophysical Research, in press

  24. Retrieval of LAI (model-based cases)

  25. Background albedo Retrievals in Visible domain Single scattering albedo LAI<4 LAI>4 RRA

  26. Leaf Area Index Single scattering albedo Asymmetry phase function VISIBLE Background albedo Single scattering albedo Near-InfraRed Asymmetry phase function Background albedo a posteriori covariance matrices Using the absorbed and scattered flux only

  27. Application results over selected EOS validation sites Application with measurements set d limited to the visible and near-infrared broadband surface albedos, i.e., 2 measurements and 7 model parameters to be retrieved

  28. prior knowledge on model parameters Pinty etal., (2007): Journal of Geophysical Research, in press

  29. a priori covariance matrix

  30. Example of application results Site identification and characteristics Pinty etal., (2007): Journal of Geophysical Research, in press

  31. Application over AGRO: Measurements Pinty etal., (2007): Journal of Geophysical Research, in press

  32. Application over AGRO: model parameters 2-stream model parameters Time-independent inversion Pinty etal., (2007): Journal of Geophysical Research, in press

  33. Application over AGRO: Radiant fluxes 2-stream model radiant fluxes Time-independent inversion

  34. a priori ‘green’ leaves in case snow occurs prior knowledge on model parameters Pinty etal., (2007): Journal of Geophysical Research, in press

  35. Application over BOREAS NSA-OBS

  36. Application over BOREAS: Measurements MODIS Snow indicator (MOD10A2) Specified uncertainty on BHRs is 5% relative

  37. Application over NSAOBS: model parameters

  38. Application over NSAOBS: model parameters MODIS /Terra FAPAR MISR /Terra FAPAR

  39. Application over NSAOBS: model parameters

  40. Application over NSAOBS: radiant fluxes

  41. Application over NSAOBS: radiant fluxes a priori ‘green’ leaves

  42. Application over NSAOBS: radiant fluxes MODIS FAPAR MERIS FAPAR JRC-FAPARSeaWiFS MISR FAPAR a priori ‘green’ leaves

  43. current inversion based on TERRA albedos Application over NSAOBS: radiant fluxes MERIS FAPAR a priori ‘green’ leaves

  44. Shrubland-woodland Deciduous broadleaf beech forest

  45. Evergreen needleleaf pine forest Deciduous needleleaf larch forest

  46. The polychrome solution The polychrome solution The GREEN solution The GREEN solution

  47. Concluding remarks 1.Computer efficient inversion package has been designed and tested : estimate of uncertainty on all retrievals 2. This integrated package can be used for various purposes : retrieval of parameters from RS products, validation of RS products, assimilation of RS products into Land surface schemes. 3. Capability to generate global surface model parameters ensuring full consistency with measured (uncorrelated) fluxes from various sources: spectral albedos from MODIS-MISR (and any other sources). 4. Estimating radiant fluxes and surface parameters in the presence of snow .

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