A Case Study for Inferring Freshwater Lake Ice Thickness by GPS Interferometric Reflectometry

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.