Ad. Friend et Pm. Cox, MODELING THE EFFECTS OF ATMOSPHERIC CO2 ON VEGETATION ATMOSPHERE INTERACTIONS, Agricultural and forest meteorology, 73(3-4), 1995, pp. 285-295
The effect of doubling atmospheric CO2 concentration (C-a) on climate
and vegetation is investigated using a combined climate-vegetation mod
el. The vegetation model predicts the response of leaf area index, can
opy transpiration (E(T)) and whole-plant carbon balance to changes in
climate, soil moisture, and atmospheric CO2 forcing. This model has be
en embedded in the UK Meteorological Office Single Column Model (SCM),
which provides the climate feedback to the vegetation. The vegetation
model uses an optimisation approach to predict stomatal resistance, a
biochemical model to predict photosynthesis and a simple carbon balan
ce model to predict leaf area. Respiration is calculated as a function
of leaf area and vegetation height. Clouds are assumed to be radiativ
ely passive in the SCM to avoid unrealistic feedbacks. Simulations wer
e performed with the fully interactive vegetation-climate model for an
Amazon location with the present-day value of C-a (1 x CO2), and twic
e this value (2 x CO2). In addition, two other types of simulation wer
e performed at both CO2 concentrations: one in which the vegetation co
mponent was forced only with 1 x CO2, and one using a fixed surface re
sistance. The latter case is equivalent to simulations using most curr
ent general circulation models. In all the simulations, increased atmo
spheric CO2 caused an increase in surface temperature owing to increas
ed radiative forcing. With a fixed resistance, mean E(T) was increased
by 5.6% and sensible heat flux was reduced by 3.8%. The fully interac
tive model had significant effects on the response of both climate and
productivity to C-a. Increased C-a caused stomatal closure, which res
ulted in a reduction in mean E(T) Of 25%. The effect of C-a on E(T) wa
s amplified by the positive feedback resulting from the effect of incr
eased air humidity deficit on stomatal resistance.