Coastal Mean Dynamic Topography Recovery Based on Multivariate Objective Analysis by Combining Data from Synthetic Aperture Radar Altimeter

MDT recovery over coastal regions is challenging, as the mean sea surface (MSS) and geoid/quasi-geoid models are of low quality. The altimetry satellites equipped with the synthetic aperture radar (SAR) altimeters provide more accurate sea surface heights than traditional ones close to the coast. We investigate the role of using the SAR-based MSS in coastal MDT recovery, and the effects introduced by the SAR altimetry data are quantified and assessed. We model MDTs based on the multivariate objective analysis, where the MSS and the recently released satellite-only global geopotential model are combined. The numerical experiments over the coast of Japan and southeastern China show that the use of the SAR-based MSS improves the local MDT. The root mean square (RMS) of the misfits between MDT-modeled with SAR altimetry data and the ocean data is lower than that derived from MDT computed without SAR data—by a magnitude of 4–8 mm. Moreover, the geostrophic velocities derived from MDT modeled with the SAR altimetry data have better fits with buoy data than those derived from MDT modeled without SAR data. In total, our studies highlight the use of SAR altimetry data in coastal MDT recovery.

High-Precision Digital Surface Model Extraction from Satellite Stereo Images Fused with ICESat-2 Data

The lack of ground control points (GCPs) affects the elevation accuracy of digital surface models (DSMs) generated by optical satellite stereo images and limits the application of high-resolution DSMs. It is a feasible idea to use ICESat-2 (Ice, Cloud, and land Elevation Satellite-2) laser altimetry data to improve the elevation accuracy of optical stereo images, but it is necessary to accurately match the two types of data. This paper proposes a DSM registration strategy based on terrain similarity (BOTS), which integrates ICESat-2 laser altimetry data without GCPs and improves the DSM elevation accuracy generation from optical satellite stereo pairs. Under different terrain conditions, Worldview-2, SV-1, GF-7, and ZY-3 stereo pairs were used to verify the effectiveness of this method. The experimental results show that the BOTS method proposed in this paper is more robust when there are a large number of abnormal points in the ICESat-2 data or there is a large elevation gap between DSMs. After fusion of ICESat-2 data, the DSM elevation accuracy extracted from the satellite stereo pair is improved by 73~92%, and the root mean square error (RMSE) of Worldview-2 DSM reaches 0.71 m.

DEM Generation with ICESat-2 Altimetry Data for the Three Antarctic Ice Shelves: Ross, Filchner–Ronne and Amery

The ice shelf is an important component of the Antarctic system, and the interaction between the ice sheet and the ocean often proceeds through mass variations of the ice shelf. The digital elevation model (DEM) of the ice shelf is particularly important for ice shelf elevation change and mass balance estimation. With the development of satellite altimetry technology, it became an important data source for DEM research of Antarctica. The National Aeronautics and Space Administration (NASA) Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) launched in 2018 is a significant improvement in along-track sampling rate and measurement accuracy compared with previous altimetry satellites. This study uses ordinary kriging interpolation to present new DEMs (ICESat-2 DEM hereinafter) for the three ice shelves (Ross, Filchner–Ronne and Amery) in Antarctica with ICESat-2 altimetry data. Two variogram models (linear and spherical) of ordinary kriging interpolation are compared in this paper. The result shows that the spherical model generally shows better performance and lower standard deviation (STD) than the linear models. The precision of the ultimate DEM was evaluated by NASA Operation IceBridge (OIB) data and compared with five previously published Antarctic DEM products (REMA, TanDEM-X PolarDEM, Slater DEM, Helm DEM, and Bamber DEM). The comparison reveals that the mean difference between ICESat-2 DEM of the Ross ice shelf and OIB is −0.016 m with a STD of 0.918 m, and the mean difference between ICESat-2 DEM of the Filchner–Ronne ice shelf and OIB is −0.533 m with a STD of 0.718 m. The three ICESat-2 DEMs show higher spatial resolution and elevation accuracy than five previously published Antarctic DEMs.

Correction of the model dynamics for the Northern seas using observational altimetry data

The earlier derived data assimilation method called Generalized Kalman filter (GKF) is applied in conjunction with the Nucleus for European Modelling of the Ocean (NEMO) circulation model to the calculation of the dynamics in the North Seas of Russia. By assimilating the satellite altimetry data from archive AVISO (Archiving, validating and interpolating of satellite observations) this method corrects the direct model calculations and improves the ocean state. The model fields, in particular, sea level and sea surface temperature with and without assimilation are constructed and compared with each other. The brief analysis of the results is also performed.

Evaluation of Marine Gravity Anomaly Calculation Accuracy by Multi-Source Satellite Altimetry Data

The purpose of this paper is to analyze the influence of satellite altimetry data accuracy on the marine gravity anomaly accuracy. The data of 12 altimetry satellites in the research area (5°N–23°N, 105°E–118°E) were selected. These data were classified into three groups: A, B, and C, according to the track density, the accuracy of the altimetry satellites, and the differences of self-crossover. Group A contains CryoSat-2, group B includes Geosat, ERS-1, ERS-2, and Envisat, and group C comprises T/P, Jason-1/2/3, HY-2A, SARAL, and Sentinel-3A. In Experiment I, the 5′×5′ marine gravity anomalies were obtained based on the data of groups A, B, and C, respectively. Compared with the shipborne gravity data, the root mean square error (RMSE) of groups A, B, and C was 4.59 mGal, 4.61 mGal, and 4.51 mGal, respectively. The results show that high-precision satellite altimetry data can improve the calculation accuracy of gravity anomaly, and the single satellite CryoSat-2 enables achieving the same effect of multi-satellite joint processing. In Experiment II, the 2′×2′ marine gravity anomalies were acquired based on the data of groups A, A + B, and A + C, respectively. The root mean square error of the above three groups was, respectively, 4.29 mGal, 4.30 mGal, and 4.21 mGal, and the outcomes show that when the spatial resolution is satisfied, adding redundant low-precision altimetry data will add pressure to the calculation of marine gravity anomalies and will not improve the accuracy. An effective combination of multi-satellite data can improve the accuracy and spatial resolution of the marine gravity anomaly inversion.

Satellite altimetry of the Barents sea

Satellite altimetry data are used for investigation of the sea level variability and sea ice cover retreat in the Barents Sea in 1992−2018. The data from ERS−1/2, ENVISAT, SARAL/AltiKa, and Sentinel-3A/3B satellites were used in this study. An increasing trend of the sea level of about 2.31 mm/yr was observed in this time period, which caused a total increase in the Barents Sea level by about 6 cm. Linear trends of the sea level change varied from 1.84 mm/yr in July to 4.29 mm/yr in September. The average velocity of the ice edge retreat along the tracks in the northeastern direction is of 10.9 km/yr for the same period. It was found that the ice edge displacement rate tends to increase by 0.30 km/yr per a degree in longitude in the eastward direction. Thus, the ice edge retreat along the “eastern” tracks goes faster than along the “western” ones, which is likely explained by a change in the water dynamics in the Barents Sea.