7.2.2.2 Convective processes
The interplay of buoyancy, moisture and condensation on scales ranging from
millimetres to tens of kilometres is the defining physical feature of atmospheric
convection, and is the source of much of the challenge in representing convection
in climate models. Deep convection is in large measure responsible for the very
existence of the troposphere. Air typically receives its buoyancy through being
heated by contact with a warm, solarheated underlying surface, and convection
redistributes the energy received by the surface upwards throughout the troposphere.
Shallow convection also figures importantly in the structure of the atmospheric
boundary layer and will be addressed in Section 7.2.2.3.
Latent heat release in convection drives many of the important atmospheric
circulations, and is a key link in the cycle of atmosphereocean feedbacks leading
to the ENSO phenomenon. Convection is a principal means of transporting moisture
vertically, which implies a role of convection in the radiative feedback due
to both water vapour and clouds. Convection also in large measure determines
the vertical temperature lapse rate of the atmosphere, and particularly so in
the tropics. A strong decrease of temperature with height enhances the greenhouse
effect, whereas a weaker temperature decrease ameliorates it. The effect of
lapse rate changes on clearsky water vapour feedback has been studied by Zhang
et al. (1994), but the significance of the lapse rate contribution (cf. item
(5) of the SAR, Technical Summary) has been somewhat exaggerated through a misinterpretation
of the paper. In fact the variation in lapse rate effects among the models studied
alters the water vapour feedback factor by only 0.25 W/(m^{2}K), or
about 10% of the total (Table 1 of Zhang et al., 1994).
There is ample theoretical and observational evidence that deep moist convection
locally establishes a “moist adiabatic” temperature profile that,
loosely speaking, is neutrally buoyant with respect to ascending, condensing
parcels (Betts, 1982; Xu and Emanuel, 1989). This adjustment happens directly
at the scale of individual convective clouds, but dynamical processes plausibly
extend the radius of influence of the adjustment to the scale of a typical GCM
grid box, and probably much further in the tropics, where the lapse rate adjusts
close to the moist adiabat almost everywhere. All convective schemes, from the
most simple Moist Adiabatic Adjustment to those which attempt a representation
of cloudscale motions (Arakawa and Schubert, 1974; Emanuel, 1991), therefore
agree in that they maintain the temperature at a nearly moist adiabatic profile.
Moist Adiabatic Adjustment explicitly resets the temperature to the desired
profile, whereas mass flux schemes achieve the adjustment to a nearadiabat
as a consequence of equations governing the parametrized convective heating
field. The constraint on temperature, however, places only a limited constraint
on the moisture profile remaining after adjustment, and the performance in terms
of moisture, clouds and precipitation may be very variable.
Since the SAR, a variety of simulations of response to CO_{2} doubling accounting
for combinations of different parametrizations have been realised with different
models (Colman and McAvaney, 1995; Yao and Del Genio, 1999; Meleshko et al.,
2000). The general effects of the convection parametrization on climate sensitivity
are difficult to assess because the way a model responds to changes in convection
depends on a range of other parametrizations, so results are somewhat inconsistent
between models (Colman and McAvaney, 1995; Thompson and Pollard, 1995; Zhang
and McFarlane, 1995). There is some indication that the climate sensitivity
in models with strong negative cloud feedback is insensitive to convective parametrization
whereas models with strong positive cloud feedback show more sensitivity (Meleshko
et al., 2000).
