Abstract

The potential for inferring freshwater lake ice thickness by using the global positioning system (GPS) is explored. In particular, lake ice thickness is estimated by using a nonlinear least squares fitting algorithm. The inputs to this algorithm are GPS signals and a simple GPS interferometric reflectometry (GPS-IR) model. The elevation angles of interest at the GPS receiving antennna are between 5 degrees and 25 degrees. A 1-day experiment with a snow-covered frozen lake using GPS satellite PRN 10 shows potential for inferring lake ice thickness by incorporating the GPS-IR model. For this satellite, the average inferred thickness (38.0 cm) slightly underestimates the in situ measurements (39.4 cm +/- 1.3 cm). GPS satellites PRN 2 and PRN 24 are also used in this study. However, their received signals did not provide the necessary information to infer a reasonable lake ice thickness.

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