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《Journal of Glaciology and Geocryology》 2005-01
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Incorporation of Global Climate Model Predictions in a Probabilistic Analysis of Thaw Penetration

Ted S. Vinson, Yoon-Shin Bae (Department of Civil, Construction and Environmental Engineering, Oregon State University, Corvallis Oregon 97331, USA)  
A probabilistic approach may be adopted to predict freeze and thaw depths to account for the variability of (1) material properties, and (2) contemporary and future surface energy input parameters (e.g. air temperatures, cloud cover, snow cover) predicted with global climate models. To illustrate the probabilistic approach, an example of the prediction of thaw depths in Fairbanks, Alaska, is considered. More specifically, the Stefan equation is used together with the Monte Carlo simulation technique to make a probabilistic prediction of thaw penetration. The simulation results indicate that the variability in material properties, surface energy input parameters, and temperature data can lead to significant uncertainty in predicting thaw penetration. The Taylor series method was performed to determine the mean and standard deviation of thaw penetration and the results were compared to the Monte Carlo simulation results. The close comparison of the results suggests that the simpler Taylor series method may be applied to many cold regions problems to account for the variability of input parameters.
【CateGory Index】: P642.14
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