nai

Project Progress

During the past year, the coupled Earth system suite of the Ent Terrestrial Biosphere Model (Ent TBM)¹, the NASA Ocean Biogeochemical Model (NOBM)², and the NASA Goddard Institute for Space Studies General Circulation Model (GISS GCM) achieved simulation of conserved carbon dynamics over seasonal cycles over 30-year late 20th century runs. However, these simulations were conducted with a simplified description of global land cover ³ that does not take into account fine structural variation within “plant functional types” that have grown in different climate zones, such that fluxes exhibit a trend that results from this vegetation map being out of equilibrium with climate variation over the globe. To provide fidelity to the existing land surface vegetation structure and geographic variation in surface fluxes, the first version of a satellite-derived global geographic vegetation structure data set was completed. This data set combines cover type, leaf area and albedo, from the Moderate Resolution Imaging Spectrometer (MODIS)⁴, forest canopy heights from the Geoscience Laser Altimeter System (GLAS) aboard the Ice, Cloud, and land Elevation Satellite(ICESat)⁵, inventories of human land uses ⁶, and several decades of 20th century climate statistics ⁷. This data set is the first attempt to introduce observed global forest heights into a global dynamic vegetation model (DGVM). Introduction of this detailed dataset, for both off-line simulations with observed meteorology as well as coupled to the GISS GCM, resulted in a fast equilibrium within three years and stable seasonal cycles.

Further refinement of the Ent TBM is still necessary to cover the full diversity of vegetation biophysical behavior and seasonal dynamics, and to reproduce the exact magnitude of latitudinal variation in the seasonal cycle of atmospheric CO₂, something that has not been satisfactorily been achieved by any DGVM yet to date. To take advantage of the diversity and canopy details that are possible now with the Ent TBM, Kiang and colleagues have commenced a large data mining effort with a newly compiled database of plant traits, the TRY database ⁸. This data mining effort aims to derive both parameter fits as well as identify new, hopefully simpler, generalizable relations between plant biophysical, phenological, and allometric quantities, as well as their geographic variation with climate. 65 researchers from around the world have granted permission to use their data, and a data set of over 3 million records has now been compiled. Preliminary example studies using linear manifold clustering on a data subset indicates a promising technique for identifying distinctions between overstory and shaded vegetation.

A proposal has also been submitted to alter the Ent TBM to simulate novel hypothetical life forms, with alternative spectral albedoes such as for red dwarf planets and tolerances for extreme climate conditions.

1. Kiang, N.Y., R.D. Koster, P.R. Moorcroft, W. Ni-Meister, and D. Rind. (2006). “Ent: A Dynamic Global Terrestrial Ecosystem Model for Coupling with GCMs,” American Geophysical Union Fall Meeting, San Francisco, CA, December 10-15, 2006.

2. Gregg, W.W., A coupled ocean general circulation, biogeochemical, and radia
tive model of the global oceans: seasonal distributions of coean chlorophyll and nutrients, 2000, NASA Goddard Space Flight Center: Greenbelt, Maryland. p. 32.
3. Matthews, E. (1983). Global vegetation and land use: new high-resolution data bases for climate studies. Journal of Climate and Applied Meteorology, 22: p. 474-487.

4. Friedl, M.A., D.K. McIver, and et.al. (2002). Global land cover mapping from MODIS: Algorithms and early results. Remote Sensing of Environment, 83(1-2): p. 287-302.

5. Simard, M., N. Pinto, J.B. Fisher, and A. Baccini. (2011). Mapping forest canopy height globally with spaceborne lidar. Journal of Geophysical Research-Biogeosciences, 116.

6. Monfreda, C., N. Ramankutty, and J.A. Foley. (2008). Farming the planet: 2. Geographic distribution of crop areas, yields, physiological types, and net primary production in the year 2000. Global Biogeochemical Cycles, 22(1): p. 19.

7. Sheffield, J., G. Goteti, and E.F. Wood. (2006). Development of a 50-yr high-resolution global dataset of meteorological forcings for land surface modeling. Journal of Climate, 19(13): p. 3088-3111.

8. Kattge, J., S. Diaz, S. Lavorel, C. Prentice, P. Leadley, G. Bonisch, E. Garnier, M. Westoby, P.B. Reich, I.J. Wright, J.H.C. Cornelissen, C. Violle, S.P. Harrison, P.M. van Bodegom, M. Reichstein, B.J. Enquist, N.A. Soudzilovskaia, D.D. Ackerly, M. Anand, O. Atkin, M. Bahn, T.R. Baker, D. Baldocchi, R. Bekker, C.C. Blanco, B. Blonder, W.J. Bond, R. Bradstock, D.E. Bunker, F. Casanoves, J. Cavender-Bares, J.Q. Chambers, F.S. Chapin, J. Chave, D. Coomes, W.K. Cornwell, J.M. Craine, B.H. Dobrin, L. Duarte, W. Durka, J. Elser, G. Esser, M. Estiarte, W.F. Fagan, J. Fang, F. Fernandez-Mendez, A. Fidelis, B. Finegan, O. Flores, H. Ford, D. Frank, G.T. Freschet, N.M. Fyllas, R.V. Gallagher, W.A. Green, A.G. Gutierrez, T. Hickler, S.I. Higgins, J.G. Hodgson, A. Jalili, S. Jansen, C.A. Joly, A.J. Kerkhoff, D. Kirkup, K. Kitajima, M. Kleyer, S. Klotz, J.M.H. Knops, K. Kramer, I. Kuhn, H. Kurokawa, D. Laughlin, T.D. Lee, M. Leishman, F. Lens, T. Lenz, S.L. Lewis, J. Lloyd, J. Llusia, F. Louault, S. Ma, M.D. Mahecha, P. Manning, T. Massad, B.E. Medlyn, J. Messier, A.T. Moles, S.C. Muller, K. Nadrowski, S. Naeem, U. Niinemets, S. Nollert, A. Nuske, R. Ogaya, J. Oleksyn, V.G. Onipchenko, Y. Onoda, J. Ordonez, G. Overbeck, W.A. Ozinga, S. Patino, S. Paula, J.G. Pausas, J. Penuelas, O.L. Phillips, V. Pillar, H. Poorter, L. Poorter, P. Poschlod, A. Prinzing, R. Proulx, A. Rammig, S. Reinsch, B. Reu, L. Sack, B. Salgado-Negre, J. Sardans, S. Shiodera, B. Shipley, A. Siefert, E. Sosinski, J.F. Soussana, E. Swaine, N. Swenson, K. Thompson, P. Thornton, M. Waldram, E. Weiher, M. White, S. White, S.J. Wright, B. Yguel, S. Zaehle, A.E. Zanne and C. Wirth. (2011). TRY – a global database of plant traits. Global Change Biology, 17(9): p. 2905-2935.