Analysis of GNSS-IR snow depth retrieval using SNR-derived interferometric phase

Abstract Global Navigation Satellite System Interferometric Reflectometry (GNSS-IR) provides scientists with an efficient method of measuring snow depth data with high spatial and temporal resolution, complementing existing snow products. The interferometric phase of the signal-to-noise ratio (SNR) is strongly correlated with the additional path delay, which is a key factor in altimetry applications. Existing altimetry applications are realized by analyzing the rate of change of the phase (i.e., the dominant frequency). However, there is a lack of in-depth exploration of the direct application of phase. Therefore, the initial focus of this study is to develop a geometric model between the interferometric phase derived from SNR and snow depth and to evaluate its performance at different stations. The secondary aim is to analyze the sensitivity of the phase to different snow states (accumulation and melting). The SNR data from three GNSS stations (PRDN, SG27, and P351) and four constellations (GPS, GLONASS, BDS, and Galileo) were analyzed. The results show that the retrieval results of the proposed method at different stations and at the same station but using different datasets are highly consistent with the conventional method, which demonstrates the feasibility and generalizability of the proposed method. For station P351, the root mean square error of the proposed method is also reduced by more than 20% compared to the conventional method. More importantly, the analysis found that the phase has the potential to identify the snow state of the reflecting surface. Also, the retrieval threshold for phase altimetry is higher relative to the conventional method. This study partially alleviates a limitation of GNSS-IR snow depth retrieval at existing stations with low antenna heights.