This paper presents a combinatorial approach for improving spatial predictions. First, copulas are used to interpolate a spatially distributed point rainfall field to a uniform spatial grid. It is observed that results vary substantially depending on the parameters chosen for interpolation leading to the hypothesis that it may be advantageous to estimate copula parameters locally or to combine local and global copula predictions. It is found that by modifying the method of forecast combinations, prediction errors in the spatial interpolation of rainfall can be reduced. Although this method of combining predictions is applied in the context of rainfall interpolation using local and global copula predictions, it can be used on other spatial variables and interpolation methods.