Abstract

Extreme-value statistics for the maximum depth of soil freezing are developed based on model-derived soil freezing estimates for the northeastern United States. The model used is shown to be quite accurate at estimating the annual maximum depth of soil freezing using only daily air temperature, snow depth, and precipitation data. These data are available from a relatively dense network of climatological observing stations, permitting the development of a regional climatology of extreme soil freezing levels. The performance of a suite of theoretical probability distributions for representing the resulting distributions of extreme soil freezing depths is also investigated, and the Gumbel distribution is chosen to provide the best regional representation of soil freezing extremes. The results suggest that maximum soil freezing levels within the northeastern United States are found across eastern Maine and north-central Pennsylvania. South of these areas, freezing levels decrease because of warmer temperatures, while to the north decreases in the depth of maximum soil freezing can be attributed to deeper and more persistent snow cover. The results provide physically based information for establishing building codes that rely on soil freezing information.

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