1. Exploitation of MODIS and MISR Surface Albedos in Support of SVAT Models LANDFLUX meeting, Toulouse, May 28-31, 2007 JRC – Ispra 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

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

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

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

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. Validation of SeaWIFS absorbed flux from in-situ estimates

7. AGRO ● JRC-FAPAR MODIS at 1.0 km ● JRC-FAPAR SeaWiFS at 2.17 km ● JRC-FAPAR MERIS at 1.2 km Validation of Ref: Turner et al. 2005 FAPAR ≈ 1.-exp(-0.5 ) from PCA_LICOR Advanced procedure for spatio-temporal changes of local LAI 2003 ● JRC FAPAR MOS at 500 m ● JRC-FAPAR SeaWiFS at 2.17 km ● JRC-FAPAR MISR at 275 m Gobron etal., (2006): Journal of Geophysical Research, doi:10.1029/2005JD006511

9. January 2001

10. MISR low & MODIS high MISR high & MODIS low

11. January 2001

12. Ratio of the mean values

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

14. 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). Needs for Land surface Models

15. Requirements from a 2-stream model 3 (effective) state variables: 1. Optical depth: LAI 2. single scattering albedo : Leaf reflectance+ Leaf transmittance 3. asymmetry of the phase function Leaf reflectance/transmittance 2 boundary conditions: 1. Top: Direct and Diffuse atmospheric fluxes (known) 2. Bottom : Flux from background Albedo (unknown) Pinty etal., (2006): Journal of Geophysical Research, doi:10.1029/2005JD005952

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

17. The concept of effective LAI Structure factor

18. Pinty etal., (2006): Journal of Geophysical Research, doi:10.1029/2005JD005952

21. Comparing/constraining or assimilating the radiation fluxes retrieved from RS against those generated by GCMs is not valid when using the true state variables in the GCMs simulations Pinty etal., (2004): Journal of Geophysical Research, doi:10.1029/2004JD005214

22. What did we improve? Domain of validity and accuracy of current implementations in GCMS: 1.can be extended to regimes where multiple scattering dominate e.g., snow-covered background. 2.Leaf reflectance can now be different from Leaf transmittance –needle shoots in coniferous canopies - 3.Corrections of current schemes in single scattering mode 4.Possibility to account for 3-D vegetation effects Possibility to ingest quantitative RS products: 1. Fluxes: Albedo, absorption 2. State variable: ‘effective’ LAI. 3.Adding one more layer to the atmospheric RT scheme

23. Needs for SVAT Models 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

24. The same RT models must be used in inverse mode and in forward mode to ensure consistency between RS products and large scale models’s simulations

25. Retrievals of model Parameters for Land surface schemes Towards an integrated system for the optimal use of remote sensing flux products 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

26. INPUTS : prior knowledge 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 RS Flux products, e.g., Albedo Vis/NIR and/or FAPAR noted

27. Optimization/assimilation scheme Model parameters 2-stream model measurements Parameter knowledge 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 Pinty etal., (2007): Journal of Geophysical Research, in press

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

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

30. Application over BOREAS NSA-OBS

31. Application over BOREAS: Measurements MODIS Snow indicator (MOD10A2)

32. Application over NSAOBS: model parameters

33. MODIS /Terra FAPAR MISR /Terra FAPAR

34. Application over NSAOBS: model parameters

35. Application over NSAOBS: radiant fluxes

36. a priori ‘green’ leaves

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

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

39. Agriculture Semi-desert

40. Deciduous broadleaf forest Shrubland-woodland

41. Deciduous GREEN broadleaf Shrubland-woodland

42. Evergreen needleleaf forest Deciduous needleleaf forest

43. Concluding remarks 1. Computer efficient inversion package has been designed and tested : assessment 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) and FAPAR from SeaWiFS/MERIS. 4. Estimating radiant flux and surface parameters in the presence of snow.