Jf. Stamm et al., SENSITIVITY OF A GCM SIMULATION OF GLOBAL CLIMATE TO THE REPRESENTATION OF LAND-SURFACE HYDROLOGY, Journal of climate, 7(8), 1994, pp. 1218-1239
The sensitivity of global climate to the characterization of the land-
surface hydrology is investigated using the Geophysical Fluid Dynamics
Laboratory GCM at R15 resolution with the standard Budyko bucket and
the Variable Infiltration Capacity (VIC) Model, which incorporates a p
arsimonious parameterization of the subgrid-scale spatial variability
of soil moisture capacity, as well as base flow, by means of soil mois
ture drainage during dry periods. Four experiments were performed usin
g the VIC model. The first used a globally fixed soil moisture capacit
y of 15 cm to provide a comparison to the Budyko bucket. The second us
ed a more realistic globally varying soil moisture capacity. The third
and fourth were sensitivity experiments using globally fixed soil moi
sture capacities of 5 and 25 cm. The results of the VIC fixed runs (15
cm) showed that global average soil moisture was considerably lower (
about 2.5 cm on average) as compared with the bucket runs, global evap
oration and precipitation were reduced, and surface air temperature wa
s increased, especially in the Northern Hemisphere in summer. The grea
ter sensitivity of the Northern Hemisphere land areas to the altered l
and hydrology is attributed primarily to recycling of summertime preci
pitation in the interior of these continents. The authors found, somew
hat surprisingly, that the water-holding capacities of the VIC model h
ad relatively little influence on the simulated climates of northern E
urasia and North America. This is attributed to the fact that much of
the soil moisture capacity is unutilized for evaporation, due to the d
ry period drainage to base flow. The results argue for representation
of the surface hydrology in GCMs with two-layer soil models, which are
capable of representing the cycling of moisture during dry periods by
means of surface evaporation, which is generally underestimated by si
ngle-layer models.