A two-step approach to sensitivity analysis of model output in large comput
ational models is proposed. A preliminary screening exercise is suggested i
n order to identify the subset of the most potentially explanatory factors.
Afterwards, a quantitative method is recommended on the subset of preselec
ted inputs. The advantage of the proposed procedure is that, very often, am
ong a large number of input factors, only a few have a significant effect o
n the model output. The approach provides quantitative sensitivity measures
while controlling the computational cost of the experiment. The procedure
has been tested on a recent version of a chemical kinetics model of the tro
pospheric oxidation pathways of dimethylsulphide, including 68 uncertain fa
ctors. (C) 1999 Elsevier Science B.V.