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The Sampling Variations of Hailstone Size Distributions

Raymond K. W. WongResource Technologies Department, Natural Resources Division, Alberta Research Council, Edmonton, Alberta, Canada

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Norman ChidambaramResource Technologies Department, Natural Resources Division, Alberta Research Council, Edmonton, Alberta, Canada

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Lawrence ChengResource Technologies Department, Natural Resources Division, Alberta Research Council, Edmonton, Alberta, Canada

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Marianne EnglishResource Technologies Department, Natural Resources Division, Alberta Research Council, Edmonton, Alberta, Canada

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Abstract

The use of a shifted gamma size distribution for hailstone samples is proposed. This is shown to provide a better fit than the usual exponential form, using time-resolved Alberta data. It is also concluded that there is a dependence of the shape of hailstone size distributions on the duration of sampling time. Such shape variations are associated with the sampling efficiency of the smaller size categories. The importance of the smaller sizes to the common hail integral estimates is also investigated. The minimum sizes required for sampling accuracy of these integral estimates are also obtained.

Abstract

The use of a shifted gamma size distribution for hailstone samples is proposed. This is shown to provide a better fit than the usual exponential form, using time-resolved Alberta data. It is also concluded that there is a dependence of the shape of hailstone size distributions on the duration of sampling time. Such shape variations are associated with the sampling efficiency of the smaller size categories. The importance of the smaller sizes to the common hail integral estimates is also investigated. The minimum sizes required for sampling accuracy of these integral estimates are also obtained.

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