Comparative analysis of GNSS-IR sea-level retrieval methods

Abstract

The Global Navigation Satellite System interferometric reflectometry (GNSS-IR) technique has been confirmed to retrieve the sea level using signal-to-noise ratio (SNR) data. To investigate the suitability of different GNSS-IR sea level retrieval methods, several strategies were tested during the data process, including: the whole arc Lomb-Scargle periodogram (whole arc LSP) method and window LSP (WinLSP) method when spectral analysis on SNR data; the tidal harmonic analysis (THA) and dynamic SNR method when using dynamic correction on retrievals; and the moving window smoothing method proposed to apply on processing of retrievals. Furthermore, the THA method is improved by segmented SNR data, and the moving window smoothing with robust local weighted regression (RLOWESS) and Savitzky-Golay (SG) filter was adopt for better serviceability. One-month data from the SC02 station were used to test all the strategies by comparing with local tide gauge records. HKQT station further verified the usability of moving window smoothing. The results confirmed that the WinLSP method can obtain more retrievals implying higher temporal resolution, but whole arc LSP method reaches better precision. The former is easily susceptible to sampling rate of SNR. Correction results of dynamic SNR method are better than that of segmented THA method. When the former is applied to retrievals of WinLSP method, the retrievals of all windows from multiple SNR arcs should be adjusted simultaneously. The moving window smoothing based RLOWESS and SG filter is more applicable to the retrievals corrected by segmented THA method, and the smoothing effect of two smoothing methods has little difference. In addition, wind speed more than 20m/s seriously affects the effect of GNSS-IR sea level retrieval. GNSS-IR technique has the potential of centimeter-level retrieved sea level.