Sea-level monitoring is important for the safety of coastal cities and analysis of ocean and climate. Sea levels can be estimated based using the global navigation satellite system–interferometry reflectometry (GNSS–IR). The frequency in a signal-to-noise ratio (SNR) arc has been found to be related to the height between the GNSS antenna and reflecting surface, which is called reflector height (RH, h). The height variation of the reflecting surface causes an error, and this error is the most significant error in the GNSS–IR sea-level retrieval. The key to the correction of height variation error lies in the determination of the RH variation rate ḣ. The classical correction method determines ḣ based on tide analysis of a coarse RH series over a longer time period. Therefore, ḣ inherits errors in coarse RH series, which contains significant bias during a storm surge, and correcting this requires data accumulation. This study proposes a correction method of height variation error based on just one SNR arc based on wavelet analysis and least-square estimation. First, using wavelet analysis, instantaneous frequencies are extracted in one SNR arc; these frequencies are then converted to RH series. Second, using least-square estimation, h and ḣ are conjointly solved based on the RH series from wavelet analysis. Data of GNSS site HKQT located in Hong Kong, China, during a period of time that includes Typhoon Hato were used. The root-mean-square errors (RMSEs) of retrievals were 21.5 cm for L1, 9.5 cm for L2P, 9.3 cm for L2C, and 7.6 cm for L5 of GPS; 16.8 cm for L1C, 14.1 cm for L1P, 12.6 cm for L2C, and 10.7 cm for L2P of GLONASS; 15.7 cm for L1, 11.2 cm for L5, 12.2 cm for L7, and 9.6 cm for L8 of Galileo. Results showed this method can correct the height variation error based on just one SNR arc, can avoid the inheritance of errors, and can be used during periods of storm surge.

No abstract

In studies concerning the surface bidirectional re ectance distribution function (BRDF) and thermal-infrared multiangular emissions, Sun-sensor geometry must be known. This Letter provides a potential and simple method for NOAA Advanced Very High Resolution Radiometer (AVHRR) users to estimate the imaging con guration of each pixel in a geometrically corrected image. Our formulas were tested with example AVHRR data and their precision was shown to be comparatively high with a maximum error of either the satellite zenith or azimuth angle less than 4°. The standard deviation for the zenith is 2.07°and azimuth is 2.47°.