The Role of Vegetation–Climate Interaction and Interannual Variability in Shaping the African Savanna

Ning Zeng Department of Atmospheric Sciences and Institute of Geophysics and Planetary Physics, University of California, Los Angeles, Los Angeles, California

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J. David Neelin Department of Atmospheric Sciences and Institute of Geophysics and Planetary Physics, University of California, Los Angeles, Los Angeles, California

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Abstract

Using a coupled atmosphere–land–vegetation model of intermediate complexity, the authors explore how vegetation–climate interaction and internal climate variability might influence the vegetation distribution in Africa. When the model is forced by observed climatological sea surface temperature (SST), positive feedbacks from vegetation changes tend to increase the spatial gradient between desert regions and forest regions at the expense of savanna regions. When interannual variation of SST is included, the climate variability tends to reduce rainfall and vegetation in the wetter regions and to increase them in the drier regions along this gradient, resulting in a smoother desert–forest transition. This effect is most dramatically demonstrated in a model parameter regime for which multiple equilibria (either a desertlike or a forestlike Sahel) can exist when strong vegetation–climate feedbacks are allowed. However, the presence of a variable SST drives the desertlike state and the forestlike state toward an intermediate grasslike state, because of nonlinearities in the coupled system. Both vegetation and interannual variability thus play active roles in shaping the subtropical savanna ecosystem.

Corresponding author address: Ning Zeng, Department of Atmospheric Sciences, UCLA, Los Angeles, CA 90095-1565.

Abstract

Using a coupled atmosphere–land–vegetation model of intermediate complexity, the authors explore how vegetation–climate interaction and internal climate variability might influence the vegetation distribution in Africa. When the model is forced by observed climatological sea surface temperature (SST), positive feedbacks from vegetation changes tend to increase the spatial gradient between desert regions and forest regions at the expense of savanna regions. When interannual variation of SST is included, the climate variability tends to reduce rainfall and vegetation in the wetter regions and to increase them in the drier regions along this gradient, resulting in a smoother desert–forest transition. This effect is most dramatically demonstrated in a model parameter regime for which multiple equilibria (either a desertlike or a forestlike Sahel) can exist when strong vegetation–climate feedbacks are allowed. However, the presence of a variable SST drives the desertlike state and the forestlike state toward an intermediate grasslike state, because of nonlinearities in the coupled system. Both vegetation and interannual variability thus play active roles in shaping the subtropical savanna ecosystem.

Corresponding author address: Ning Zeng, Department of Atmospheric Sciences, UCLA, Los Angeles, CA 90095-1565.

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  • Bonan, G. B., D. Pollard, and S. L. Thompson, 1992: Effects of boreal forest vegetation on global climate. Nature,359, 716–718.

  • Brovkin, V., M. Claussen, V. Petouknov, and A. Ganopolski, 1998: On the stability of the atmosphere–vegetation system in the Sahara/Sahel region. J. Geophys. Res.,103, 31 613–31 624.

  • Charney, J. G., 1975: Dynamics of deserts and droughts in Sahel. Quart. J. Roy. Meteor. Soc.,101, 193–202.

  • Claussen, M., 1994: On coupling global biome models with climate models. Climate Res.,4, 203–221.

  • ——, 1998: On multiple solutions of the atmosphere–vegetation system in present-day climate. Global Biogeochem. Cycles,4, 549–559.

  • ——, and Coauthors, 1998: Modelling global terrestrial vegetation–climate interaction. Philos. Trans. Roy. Soc. London,353B, 53–63.

  • Dickinson, R. E., and A. Henderson-Sellers, 1988: Modeling tropical deforestation: A study of GCM land-surface parameterizations. Quart. J. Roy. Meteor. Soc.,114, 439–462.

  • ——, M. Shaikh, R. Bryant, and L. Graumlich, 1998: Interactive canopies for a climate model. J. Climate,11, 2823–2836.

  • Ellis, J. E., and D. M. Swift, 1988: Stability of African pastoral ecosystems: Alternate paradigms and implications for development. J. Range Manage.,41, 450–459.

  • Foley, J. A., and Coauthors, 1996: An integrated biosphere model of land surface processes, terrestrial carbon balance, and vegetation dynamics. Global Biogeochem. Cycles,10, 603–628.

  • ——, and Coauthors, 1998: Coupling dynamic models of climate and vegetation. Global Change Biol.,4, 561–579.

  • Folland, C. K., T. N. Palmer, and D. E. Parker, 1986: Sahel rainfall and worldwide sea temperatures, 1901–85. Nature,320, 602–607.

  • Ganopolski, A., and Coauthors, 1998: The influence of vegetation–atmosphere–ocean interaction on climate during the mid-Holocene. Science,280, 1916–1919.

  • Goward, S. N., and S. D. Prince, 1995: Transient effects of climate on vegetation dynamics—satellite observations. J. Biogeogr.,22, 549–564.

  • Henderson-Sellers, A., 1993: Continental vegetation as a dynamic component of a global climate model: A preliminary assessment. Climatic Change,23, 337–378.

  • Ji, J.-J., 1995: A climate–vegetation interaction model: Simulating physical and biological processes at the surface. J. Biogeogr.,22, 445–451.

  • Lean, J., and D. A. Warrilow, 1989: Simulation of the regional climatic impact of Amazon deforestation. Nature,342, 411–413.

  • Lieth, H., 1975: Modeling the primary productivity of the world. Primary Productivity of the Biosphere, H. Leith and R. H. Whittaker, Eds., Springer-Verlag, 237–263.

  • Neelin, J. D., and N. Zeng, 2000: A quasi-equilibrium tropical circulation model—formulation. J. Atmos. Sci.,57, 1741–1766.

  • Nicholson, S. E., C. J. Tucker, and M. B. Ba, 1998: Desertification, drought, and surface vegetation: An example from the West African Sahel. Bull. Amer. Meteor. Soc.,79, 815–829.

  • Prentice, I. C., W. Cramer, S. P. Harrison, R. Leemans, R. A. Monserud, and A. M. Solomon, 1992: A global biome model based on plant physiology and dominance, soil properties and climate. J. Biogeogr.,19, 117–134.

  • Reynolds, R. W., and T. M. Smith, 1994: Improved global sea surface temperature analyses using optimum interpolation. J. Climate,7, 929–948.

  • Schimel, D. S., VEMAP participants, and B. H. Braswell, 1997: Continental scale variability in ecosystem processes: Models, data, and the role of disturbance. Ecol. Monogr.,67, 251–271.

  • Sellers, P. J., and Coauthors, 1996: A revised land surface parameterization (SiB2) for atmospheric GCMs. Part I: Model formulation. J. Climate,9, 676–705.

  • Shukla, J., C. Nobre, and P. Sellers, 1990: Amazon deforestation and climate change. Science,247, 1322–1325.

  • Sud, Y. C., G. K. Walker, J.-H. Kim, G. E. Liston, P. J. Sellers, and W. K.-M. Lau, 1996: Biogeophysical consequences of a tropical deforestation scenario: A GCM simulation study. J. Climate,9, 3225–3247.

  • Wang, G., and E. A. B. Eltahir, 2000: Biosphere–atmosphere interactions over West Africa. 2. Multiple climate equilibria. Quart. J. Roy. Meteor. Soc., in press.

  • Woodward, F. I., 1987: Climate and Plant Distribution. Cambridge University Press, 174 pp.

  • Xue, Y., and J. Shukla, 1993: The influence of land surface properties on Sahel climate. Part I: Desertification. J. Climate,6, 2232–2245.

  • Zeng, N., J. D. Neelin, W. K.-M. Lau, and C. J. Tucker, 1999: Enhancement of interdecadal climate variability in the Sahel by vegetation interaction. Science,286, 1537–1540.

  • ——, ——, and C. Chou, 2000: A quasi-equilibrium tropical circulation model—implementation and simulation. J. Atmos. Sci.,57, 1767–1796.

  • Zhang, H., A. Henderson-Sellers, and K. McGuffie, 1996: Impacts of tropical deforestation. Part I: Process analysis of local climatic change. J. Climate,9, 1497–1517.

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