GNSS-IR-Based Snow Depth Estimation: A Case Study for CRIOS Network on Svalbard

Among the different approaches to the use of surface-reflected Global Navigation Satellite Systems (GNSS) signals in Earth sciences is GNSS Interferometric Reflectometry (GNSS-IR), which allows the measurement of the distance between a GNSS antenna and a reflecting surface by analyzing the time-series variations of the signal-to-noise ratio (SNR) parameter. This method can be used to monitor changes in the height of the reflecting surface, including the depth of snow cover. The study presents, for the first time, the application of GNSS-IR to snow cover monitoring in the Svalbard region, based on data from three monitoring stations of the CRIOS network. The article presents the methodology for data processing and determination of the snow depth parameter and validation of the obtained results based on in-situ measurements. Additionally, the study includes a detailed analysis of the suitability of the most frequently used observation types in all four Multi-GNSS constellations. For the one-year period studied (between September 2023 and August 2024), the mean error of snow depth estimation was on the order of a few centimetres, with a median of daily standard deviations in the range of 2.4–5.4 cm and correlation coefficients with manual and automatic measurements in the range of 0.83–0.93. A similar suitability for estimating the snow depth parameter was observed for all tested types of Multi-GNSS observations, with a slight advantage for L5 signals. This case study enables the enhancement of polar research conducted by field scientists by offering GNSS-IR as an automated alternative to traditional manual snow depth measurements.