Abstract

Compared with tide gauges, Global Navigation Satellite System Multipath Reflectometry (GNSS-MR) can provide low-cost, long-term sea-level data that are not susceptible to crustal loading. Signal-to-noise ratio (SNR) observables in GNSS files are commonly used for GNSS-MR; however, these observables are not always present, especially in early GNSS files. Several different combinations of codes and carrier-phases for GNSS-MR as substitutes to extract sea level have been proposed; however, the requirement of these methods for application of cycle slip detection or multi-frequency observations to isolate multipath signals reduces their applicability. Here, we propose a new method for sea-level estimation using Signal Strength Indicator (SSI) data in GNSS observation files, which is an alternative to existing methods because SSI data always exist. To verify the proposed method, we used four multi-GNSS data from three stations to monitor sea level. Sea-level estimations with root-mean-square errors of 7–8, 5–9, 12–15 and 9–13 cm relative to in-situ data were retrieved, and the correlation coefficients for these stations were bigger than 0.98, 0.98, 0.93 and 0.96, respectively. Moreover, the proposed method measures sea levels with precision similar with the traditional SNR method. In addition, sea-level results derived from the proposed method at these stations were further applied to estimate ocean tides. Ocean-tide coefficients for several main tides determined by different data were in good agreement.

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