Forrest G. Hall 1 Thomas Hilker 1 Compton J. Tucker 1 Nicholas C. Coops 2 T. Andrew Black 2

1. Data assimilation of photosynthetic light-use efficiency using multi-angular satellite data • Forrest G. Hall1 • Thomas Hilker1 • Compton J. Tucker1 • Nicholas C. Coops2 • T. Andrew Black2 • Caroline J. Nichol3 • Piers J. Sellers1 • 1NASA Goddard Space Flight Center Greenbelt, MD, USA • 2University of British Columbia, Vancouver, BC Canada • 3University of Edinburgh, Edinburgh EH9 3JN, UK

2. CARBON, WATER & ENERGY CYCLE ENERGY CYCLE CARBON CYCLE PAR PHOTOSYNTHETIC RATE Gross Primary Production GPP = PAR xFparxe Net Primary Production NPP = GPP – Respiration Light Use Efficiency mol C/ mol photon R = GPP – NPP spectral eddy corr Evapotranspiration ET = Transpiration + Evaporation NPP eddy corr gcga GPP T ~[e*- ea] R Nightime Temp based gc+ga GPP = NPP - R • gc = a + bGPP x(h/c) WATER CYCLE

3. 0.15 0.10 reflectance 0.05 0.50 0.55 0.60 wavelength (m) Associated changes in reflectance leaf structure and leaf area 1 0.8 0.6 0.4 0.2 0 pigments water absorption ζ ] = Δ reflectance 531nm 570nm 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4 wavelength(µm)

4. Multi-angle Remote Sensing of ε AMSPEC 256 bands 350-1200nm 10nm bandwidth Hilker et al., Remote Sensing of Environment (2010)

5. Effects of Functionon Canopy PRI Insensitive to ς Δρ@531nm from down-regulation) PRI’ shaded sunlit shaded Unstressed canopy PRI ε low high ε = high ε= low Hall et al. Rem. Sens. Environ. (2008,2012)

6. Orbital Canopy PRI’ and ε PRI’ = PRI’max <PRI’> shaded sunlit shaded Ground Track ε = εopt ε = high ε X 4 3 2 1 low high ε= low 3 4 1 2 Hall et al. Rem. Sens. Environ. (2008,2012)

7. Differences Among Test Sites Hilker et al., Journal of Geophysical Research (2011)

8. Satellite-derived Photosynthesis (PRI’) Hilker et al., Journal of Geophysical Research (2011)

9. Remote sensing of ε across sites1st derivative of PRI (wrtαs) vs. ε AMSPEC Spectrometer Based Tower-Based

10. TemporalScaling of Photosynthesis Data assimilation εopt (t3) εopt (t2) εopt (t1) εopt εopt (tn) Spectrally Derived Instantaneous Diurnal Spatially Explicit Time Series Hilker et al., Remote Sensing of Environment (submitted)

11. Two years of Ɛopt from CHRIS-PROBA εopt 10/01/06 06/04/06 08/26/06 08/02/07 10/27/06 07/06/07 07/06/06 time

12. Hall et al. RSE (2012) Response functions

13. Model comparison: GPP MODIS GPP model: Tower fPAR, PAR, MODIS ɛ Data assimilation model: Tower fPAR, PAR, assimilated ɛ Hilker et al. RSE (2012)

14. Comparing Fluxes: EC, MODIS, Data assimilation model Assimilation Hilker et al. RSE (2012)

15. Respiration NEP GEP GPP=NPP-R We can determine R independently of TSoil Hilker et al. Ag and For Met (2012)

16. Diurnal variability of R Hilker et al. Ag and For Met (2012)

17. Energy balance Hilker et al. GCB (2012)

18. Energy Balance: λE Hilker et al. GCB (2012)

19. Energy Balance(spectral) λE+H = (tower)RN- G ? Hilker et al. GCB (2012)

20. Recent relevant publications: Hall, F.G., et al., N.C., 2012. Data assimilation of photosynthetic light-use efficiency using multi-angular satellite data: I. Model formulation. Rem. Sens. Environ., 121: 301–308. Hilker, T. et al., 2012a. Data assimilation of photosynthetic light-use efficiency using multi-angular satellite data: II Model implementation and validation. Rem. Sens. Environ., 121: 287–300 Hilker, T. et al., 2012b. A new technique for estimating daytime respiration of forest ecosystems. Agr. For. Met. Hilker, T. et al., 2012c. On the Remote Sensing of Heat Fluxes and Surface Energy Balance. Global Change Biology. Hilker, T. et al., 2011. Inferring terrestrial photosynthetic light use efficiency of temperate ecosystems from space. JGR-Biogeosc., 116. Hall, F.G. et al., 2011. PHOTOSYNSAT, photosynthesis from space: Theoretical foundations of a satellite concept and validation from tower and spaceborne data. Rem. Sens. Environ., 115(8): 1918-1925. Hilker, T. et al., 2010. Remote sensing of photosynthetic light-use efficiency across two forested biomes: Spatial scaling. Rem. Sens. Environ., 114: 2863–2874. Hall, F.G. et al., 2008. Multi-angle remote sensing of forest light use efficiency by observing PRI variation with canopy shadow fraction. Rem. Sens. Environ., 112(7): 3201-3211.

21. Conclusions • PRI’ quantifies light use efficiency (LUE) independent of ecosystem variations in canopy structure and unstressed reflectance. • Near instantaneous multi-angle data are required to simultaneously quantify PRI and shadow fraction. • For the first time we have an eddy-correlation independent, spectral method to quantify GPP from towers and space. • Used in a data assimilation mode with GPP model, our satellite GPP algorithm can provide high spatial resolution, diurnal estimates of GPP. • The ability to infer light use efficiency at regional scales allows us also to infer respiration independently of Tsoil and • To remotely sense the key components of the surface energy balance. • A network of AMSPEC sites (@≈30k ea) could help rapidly refine process understanding and modeling in other ecosystems.

22. Recommendations • A wide-swath (~700km) satellite (along track multi-angle viewing) with PRI bands, chlorophyll absorption and NIR bands (for Fpar) could provide important advancements in the quantification and understanding of the global carbon, water and energy cycle.

23. Spaceborne photosynthesis Figure: NASA Goddard Space Flight Center