Does the Inclusion of Realistic Vegetation Make for Healthier Climate Models?

It is common knowledge that weather and climate have an impact on vegetation that grows on land. What is not commonly known is that vegetation can, in turn, influence weather and climate since vegetation can affect the surface energy budget and wind fields. One of the major problems in simulating the climate is the exchange of heat and mass between the atmosphere, ocean, land masses, and ice masses.

Vegetation can influence the amount of solar energy absorbed and reflected (albedo) at the surface. This impacts heating and evaporation at the surface. Plants also "perspire" water vapor which then influences the amount of water vapor in the air and water mass in the soil. The characteristics of plants, including their height, density, and even leaf characteristics, can influence the wind profile near the surface. This influences near-surface mass, momentum, and energy transports.

A study performed by Delire et al. (2011) at Meteo-France in Toulouse used the CCMv3 and LMDz atmospheric GCMs and coupled these models to the latest versions of the Integrated Biosphere Simulator (IBIS) (Foley et al. 1996) and the ORCHIDEE biosphere model (Krinner et al. 2005), respectively. Each is a land surface model that includes plant characteristics such as the physiology of plant cover, plant phenology, carbon cycling, plant type competition, photosynthesis, and respiration. Both include daily and annual vegetation cycles and distinguish between trees and other types of vegetation (grasses, shrubs). Delire et al. (2001) ran each model with full capabilities and by keeping the vegetation constant (Fixed).

The GCM modeling strategy used by Delire et al. (2011) was to simulate the climate using observed sea surface temperatures from 1870 - 1899 available from the Hadley Centre in England. The goal here was to remove the impact of the ocean in order to guarantee that land-surface process differences in both coupled systems could be highlighted. The model was run for 400 years, and the last 300 were used for analysis.

The interannual variability in plant cover generated by both models was similar to that of observed plant cover variability derived using satellite observations from 1982-1994. The LMDz-ORCHIDEE model showed stronger interannual variability, but in both the variability in tree cover was less than 5%, while for grasses it could be as much as 10-20%. Vegetation, in turn, impacted on climate, as inferred by comparing the dynamic to fixed vegetation. The model strategy above precludes comparison with observed climate.

The dynamic vegetation runs showed stronger low frequency variability than the fixed runs for both temperature and precipitation for each model system, but the disparity between the fixed and dynamic run was stronger for the CCMv3-IBIS system (Fig.1). Then the strength of the variability from these experiments (0.05 - 2.0°C) compared favorably to that inferred by previous studies. The feedback between temperature and plant growth is generally positive (warmer temperatures, increased vegetation) in the mid-latitudes and poleward. The feedback is generally negative and weaker in semi-arid regions (increased vegetation, more evaporation, cooler temperatures). There was only a weak positive feedback in the precipitation over most areas of the globe.

As we begin to understand more about the climate system, including the complexity of heat and mass exchange between various parts of the climate system, we can more effectively model the past climate including its variability. Many of the climate simulations used to project future climate are fairly simple models that do not include a dynamic ocean or realistic representations of biological processes on land. These are issues that cannot be ignored or overlooked. As Delire et al. (2011) state; "Terrestrial ecosystems provide 'memory' to the climate system, causing important variations in the climate and ecological conditions on long-time-scales."

Additional References
Foley, J.A., Prentice, C.I., Ramankutty, N., Levis, S., Pollard, D., Sitch, S. and Haxeltine, A. 1996. An integrated biosphere model of land surface processes, terrestrial carbon balance, and vegetation dynamics. Global Biogeochemical Cycles 10: 603-628.

Krinner, G., Viovy, N., de Noblet-Ducoudré, N., Ogée, J., Polcher, J., Friedlingstein, P., Ciais, P., Sitch, S. and Prentice, I.C. 2005. A dynamic global vegetation model for studies of the coupled atmosphere-biosphere system. Global Biogeochemical Cycles 19: 1-33.