A screening method proposed by Morris has been applied to a model of the oceanic production of dimethylsulfide (DMS), an important sulphur-containing gas which plays an important role in climate regulation. The model is usually refered as the GMSK (Gabric-Murray-Stone-Kohl) model and it is described by Gabric et al. (1993, 1996). The aim of the experiment is to quantify the relative importance of some pre-selected input factors in determining the predicted value of a model state variable: the DMS annual flux. The method is based on an experimental plan, composed of individually randomised one-factor-at-a-time designs, with the purpose of collecting random samples from the distribution of ''elementary effects'', denoted by F-i, associated with each input parameter. A large (absolute) measure of central tendency for F-i indicates an input with an overall influence on the output. A large standard deviation indicates an input whose influence is highly dependent on the values of the other inputs -i.e., one involved in interactions or whose effect is nonlinear. In particular, estimates of the means and standard deviations of these distributions will be used as indicators of which inputs should be considered important. Five of the total number of factors involved in the GMSK model have been examined. The selected factors are: the maximum nitrate uptake by phytoplankton (k23 in the model), the algal S:N (sulphur to nitrogen) ratio (gamma in the model), the parameter involved in the link phytoplankton-protozoa (k3), the initial mixed layer nitrogen concentration (DIN), and the sea surface temperature (SST). The experimental results show that none of the parameters studied has both mean and standard deviation close to zero, that is they all have a direct or indirect effect on the output, confirming that the DMS flux prediction is indeed sensitive to these parameters.
