SPATIAL INTERPOLATION ERRORS FOR MONITORING DATA

Separate modeling of the spatial mean field, the spatial variance fiel d, and the space-time residual fields can give a more detailed and pos sibly more accurate representation of spatial interpolation errors whe n we have repeated observations on a fixed monitoring network. This ar ticle gives expressions for the spatial interpolation errors in terms of the statistics of the component fields, which enable us to assess t he relative importance of different kinds of uncertainty. This modelin g approach is applied to data of sulfur dioxide concentrations in Euro pe, and a comparison with neighborhood kriging is done by means of cro ss-validation.