Thermal Ice Growth: Real-Time Estimation

Abstract

The quasi-steady thermal ice growth model was recast in state-space form and used with the Kalman filter to estimate ice thickness and to recursively estimate the model parameters for thermal ice growth. This approach was appropriate at locations where measurements of the ice thickness were made during the study. The model was applied to two widely separated sites from which ice thickness measurements were available for a number of winters: Post Pond, N.H., and Snowshoe Lake, Alaska. The parameters required by the Kalman filter were estimated through numerical experiments and were consistent between both locations. The Kalman filter was able to produce better results, as measured by a least-squares criterion, than a model using parameter values that had been determined using all data at each location.