Stochastic interpolation of rainfall data from rain gages and radar using cokriging: 1. Design of experiments

Abstract

Cokriging is used to merge rain gage measurements and radar rainfall data. The cokriging estimators included are ordinary, universal, and disjunctive. To evaluate the estimators, two simulation experiments are performed. The first experiment assumes that high‐quality radar rainfall fields are ground truth rainfall fields. From each ground truth rainfall field, multiple combinations of rain gage measurement field and radar rainfall field are artificially generated with varying gage network density and error characteristics of radar rainfall. The second experiment uses a stochastic space‐time rainfall model to generate assumed ground truth rainfall fields of various characteristics. Due to the sparsity of rain gage measurements, the second‐order statistics required for cokriging can only be estimated with large uncertainty. The adverse effects of this uncertainty, and the point sampling error of rain gage measurements are explicitly assessed by cokriging the ground truth rainfall data and the radar rainfall data with near perfectly known second‐order statistics.