This paper shows and describes the results from an extensive cross validation of estimated and observed rains, as well as for theoretical and observed standard errors. The cross validation demonstrates the unbiasedness of the gridded product and is used to develop a statistical model of interpolation error based on relationships between the actual distributions of interpolation errors and theoretical distributions of Kriging errors. The resulting model provides a tool for estimating uncertainty due to interpolation throughout the grid domains.
The uncertainty estimation procedure is explained in detail and spatial distributions of quantile thresholds are shown. Errors due to data sparseness, heteroscedasticity and departures of raw rainfall distributions from the normal are discussed along with the effects of increasing averaging scales on uncertainty estimates. In addition, procedures for training and validation site selection, for semivariogram model parameter training, and for the Kriging scheme are shown. The overall results of this effort illustrate the potential usefulness of the gridded atoll product, as well as provide a way to gauge the accuracy of the individual values.