Abstract
Haifall data collected from a fixed network in northeastern Colorado during three seasons (1960–62) included the estimated impact energy, duration of hailfall, most common stone size, maximum stone size, and number of stones per square inch. These basic data,X, along with the transformations, lnN, √X, 3√X, and 1/X were analyzed by computer methods to determine which parameters could be used in a statistical analysis of hail suppression experiment. The gamma distribution function was fitted to the hailfall data by the method of maximum likelihood. A chi-square goodness of fit test was applied to the data, and one transformation was tested using a sequential analysis technique.
All parameters except impact energy and number of hailstones per square inch were eliminated from the statistical analysis because of bias, non-homogeneity, or sparsity of samples. Transformations which produced the minimum mean coefficient of variation were logarithm of impact energy (InE) and square root of the number of stones per square inch (√N1 − 6). It was determined that a target-control analysis was not feasible for the analysis of hail suppression experiment. A period of 3 to 5 years is believed necessary to detect changes of 10 to 25 per cent in the hail parameters. The gamma distribution function fitted only the √N1 − 6 data. From the results it was concluded that a sequential analysis test alone could not adequately evaluate the effectiveness of a hall modification experiment.
