9A.5 An Evaluation of a Procrustes Shape Analysis Verification Tool Using Idealized Cases

A recently developed verification tool designed by the Department of Statistics at the University of MissouriColumbia was evaluated utilizing several idealized cases. The verification methodology utilizes a Procrustes fit for shape analysis of individual cells (Dryden and Mardia, 1998). The scheme also includes statistics based on intensity parameters for a complete verification solution. The information on the error based on size, translation, and rotation are combined with error based on intensity values via a penalty function. As the errors are residual sum of squares they are open-ended and this testing procedure allows the assessment of the scale such that (1) different forecast situations can be compared, (2) comparability can be achieved between the different components that make up the total error, and (3) suitable normalization factors can be found that take the previous issues into account to create a robust and practical verification scheme.