Calibration/Validation (Cal/Val) of satellite altimeters is fundamental for monitoring onboard sensor performance and ensuring long-term data quality. As altimeter technology has been evolving rapidly from profile to wide swath and interferometric altimetry, different requirements regarding Cal/Val have emerged. Most current Cal/Val technology has been developed for conventional profile altimeters, whereby satellite observations are compared against measurements at one point along orbit lines. However, the application of this type of Cal/Val technique to swath interferometric altimeters with two-dimensional measurements is difficult. Here, we propose a new strategy for the evaluation of interferometric altimeters based on comparison of wave-induced sea surface elevation (WSSE) spectra from one- and two-dimensional measurements. This method assumes that the WSSE variance of an equilibrium wave field is uniform and can be measured equivalently in the space or time domains. The method was first tested with simulated data and then used to evaluate the performance of an airborne interferometric radar altimeter system (AIRAS) using Global Navigation Satellite System (GNSS) buoy measurements. The differences between the WSSE variances from the AIRAS and two GNSS buoys were below 8 cm², corresponding to a standard deviation of 2.8 cm, which could serve as a reference for the WSSE error over the scale range of waves. The correlation coefficient between the AIRAS and GNSS buoys was approximately 0.90, indicating that the error was small relative to the WSSE signals. In addition, the sea surface height (SSH) difference measured by the AIRAS was compared with that derived from the GNSS buoys at two sites. The results indicated that the error of the SSH difference was 3 cm. This approach represents a possible technique for the Cal/Val of future spaceborne/airborne interferometric altimeters; however, additional experiments and applications are needed to verify the feasibility of this method.

Validating the wet path delay (WPD) is essential to determining satellite microwave radiometer errors that may deteriorate sea level measurement accuracy. The global navigation satellite system (GNSS) is a favored method for assessing WPD for altimetry. Over Chinese coastal waters, however, validations have not been performed, primarily because of the large gaps between International GNSS Service sites. Herein, we report a long-term assessment of the Jason-2/3 radiometers and the initial performance of the Chinese HY-2B radiometer via comparisons of WPD values derived from three types of GNSS networks along the Chinese coast. A new method based on the second-order derivative of WPD along satellite tracks was developed to detect where land contamination first appears. The results indicate that this method is more sensitive to land influences; the distance at which land contamination first appears was estimated to be approximately 40–50 km over the China coast sea. To compare the WPD at different heights, such as GNSS sites and sea level surface, an exponential function containing the corresponding decay coefficients was adopted. The WPD decay coefficients for each GNSS site were recalculated using the 3-D ERA5 pressure level fields instead of the empirical value of 2000. The results show that the new coefficient may reduce the differences between WPD values at different heights. This WPD comparison over Chinese coastal waters indicates average WPD differences of 3 (Jason-2) and −1 mm (Jason-3), showing a high level of consistency between the GNSS sites and the satellite radiometers. The uncertainties in the WPD differences were estimated to be 14–21 and 7–24 mm for the Jason-2/3 and HY-2 radiometers, respectively, which is consistent with previous studies using global GNSS. After removing the GNSS uncertainty and the spatial decorrelation, the WPD uncertainties of the Jason-2, Jason-3, and HY-2 radiometers over the regional area were estimated to be 13, 14, and 11 mm, respectively. The long-term evaluation of the WPD differences with the GNSS sites indicates that the drift rates of the Jason-2/3 radiometers over China coast waters are 0.3 and −0.9 mm/y, respectively.

On 15 January 2022, a violent eruption and tsunami of the Hunga Tonga-Hunga Ha’apai (HTHH) volcano in Tonga, South Pacific, caused widespread international concern. In order to detect the anomalous environmental response caused by the HTHH volcanic eruption based on GNSS ionospheric data, GNSS tropospheric data and GNSS coordinate time series, a new method combining the zenith non-hydrostatic delay difference method and the extreme-point symmetric mode decomposition (ESMD) method, was proposed to detect tropospheric anomalies. The moving interquartile range method and the ESMD method were introduced to detect ionospheric anomalous and coordinate time series anomalies, respectively. The results showed that 9–10 h before the eruption of the Tonga volcano and 11–12 h after the eruption of the Tonga volcano, obvious total electron content (TEC) anomalies occurred in the volcanic eruption center and its northeast and southeast, with the maximum abnormal value of 15 TECU. Significant tropospheric anomalies were observed on the day of the HTHH volcano eruption as well as 1–3 days and 16–17 days after the eruption, and the abnormal intensity was more than 10 times that of normal. The coordinate time series in direction E showed very significant anomalies at approximately 2:45 p.m. on 14 January, at approximately 4:30 a.m.–5:40 a.m. on 15 January, and at approximately 3:45 a.m. on 16 January, with anomalies reaching a maximum of 7–8 times daily. The abnormality in the direction north (N) is not obvious. Very prominent anomalies can be observed in the direction up (U) at approximately 4:30 a.m.–5:40 a.m., with the intensity of the anomalies exceeding the normal by more than 10 times. In this study, GNSS was successfully used to detect the anomalous environmental response during this HTHH volcano eruption.

Global Navigation Satellite System (GNSS) buoys were used to retrieve the significant wave heights (SWHs) and dominant periods of waves in the Qingdao coastal waters off China. The precise point positioning (PPP) and postprocessed kinematic (PPK) techniques were used to obtain the absolute motion of the GNSS buoys. Even though PPP has relatively low absolute positioning accuracy, this accuracy has a minimal influence on the spectrum in the wave frequency band. SWH values calculated from the PPK and PPP modes are nearly identical, with correlation coefficients and symmetric regression slopes both higher than 0.99. The SWH values calculated from PPP also show good agreement with a dedicated wave buoy, with a correlation coefficient of 0.935 and a difference of 0.82 cm ± 4.63 cm. A GaoFen-1 satellite image was used to assess the GNSS PPP wave spectrum via the dispersion relationship; both exhibit wave spectra with two peaks, consistent with the wave characteristics in the area.

To address challenges in large-scale deployments and real-time wave observations using GNSS buoys, we assessed the reliability and precision of the single-frequency L1 Time-Differenced Carrier Phases (TDCP) method for determining significant wave heights (SWH) and average wave periods. Utilizing simulated dynamic velocity measurements derived from International GNSS Service static observations, our study demonstrates that the L1 TDCP method exhibits superior performance compared to dual-frequency TDCP, Post-Processed Kinematic (PPK), and Doppler algorithms. Notably, L1 TDCP achieves approximately five times greater precision than the Doppler method in vertical direction assessments. In the offshore waters of Qingdao, China, we deployed two GNSS buoys for wave observation experiments, complemented by a nearby accelerometer-equipped wave buoy for external validation. By integrating the velocity measurements obtained from L1 TDCP, we derived the sea surface displacement, which, after applying a high-pass filter, isolated the wave components. The experimental results confirmed a strong correlation between L1 TDCP and PPK methods in capturing SWH and wave periods. The study found a negligible difference between L1 TDCP and PPK in SWH (0 ± 7.1mm, 99% correlation) and in average wave period (0 ± 0.13s, 97% correlation). The wave observations from two independent GNSS buoys at the same location also exhibited remarkable consistency, with a difference in SWH of 0.0 ± 2.5cm and in average wave period of 0.0 ± 0.1s. Compared to the independent wave buoy, the L1 TDCP method demonstrated a difference in SWH of -1.9 ± 5.8cm with a 93% correlation, and in average period of 0 ± 0.1s with a 94% correlation. Further, our analysis into GNSS data sampling frequencies highlighted the efficacy of 1Hz GNSS data in wave inversion, though certain spectral limitations were noted. Implementing the L1 TDCP method at 1Hz offers a substantial reduction in associated hardware costs, storage requirements, and computational demands. Notably, in contrast to PPK, it negates the need for delayed precise ephemeris, facilitating real-time computations. This study highlights the potential of L1 TDCP for broader, real-time GNSS buoy wave observations, harmonizing with the United Nations Decade of Ocean Science’s aspirations for an augmented Global Ocean Observing System.

Tropical cyclones (TCs) drive both storm surge and anomalous ocean currents, yet the spatial structure of TC-induced current anomalies remains unquantified from multi-station observations. Here we analyze 12 years of surface current and tidal gauge data from the coastal network around Taiwan Island spanning 89 TC events and 297 event-station pairs. TC-induced current anomalies display systematic spatial patterns governed by TC passage direction: TCs passing north of Taiwan Island produce southwestward anomalous currents along the western coast and Taiwan Strait, consistent with channeled Ekman transport, while the eastern and southern coasts respond with distinct directions reflecting local wind field asymmetry. TCs passing south generate more heterogeneous patterns with weaker anomalies across the network. Current anomaly magnitudes scale with TC intensity, r = 0.317, p < 0.001, and storm surge and current anomaly time series are temporally uncorrelated, r = 0.039, indicating independent dynamical pathways despite shared atmospheric forcing. These results establish a multi-station observational baseline for TC-driven current forecasting around Taiwan Island.