Spatial Statistics Preserving Interpolation Methods for Estimation of Missing Precipitation Data

Spatial interpolation methods used for estimation of missing precipitation data at a site seldom check for their ability to preserve site and regional statistics. Such statistics are primarily defined by spatial correlations and other site-to-site statistics in a region. Preservation of site and regional statistics represents a means of assessing the validity of missing precipitation estimates at a site. This study will evaluate the efficacy of traditional deterministic and stochastic interpolation methods aimed at estimation of missing data in preserving site and regional statistics. New optimal spatial interpolation methods that are intended to preserve these statistics are also proposed and evaluated in this study. Rain gauge sites in the state of Kentucky, USA, are used as a case study for evaluation of existing and newly proposed methods. Several error and performance measures will be used to evaluate the methods and trade-offs in accuracy of estimation and preservation of site and regional statistics.