A Multivariate Methodology for the Analysis of Weather Modification Experiments.
FLORIDA STATE UNIV TALLAHASSEE DEPT OF STATISTICS
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This paper develops applications of multivariate statistical models, particularly principal component analysis, to the analysis of data from weather modification experiments. The efficacy of these multivariate applications is examined by applying the proposed models to data from Phase I of the Santa Barbara Convective Band Seeding Program conducted for the Navy by North American Weather Consultants. Multivariate summary measures of precipitation are developed and multivariate methods are given to analyze the effects of cloud-seeding on precipitation. Results from these models, based on the above-mentioned data set, are reported along with conclusions and suggestions for further work. An appendix provides detailed summary statistics for the analyses. Author