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Objectives: Backscatter coefficient (σ 0) is one of observations of satellite radar altimetry, which is widely used in the processes of surface state monitoring, snow thickness inversion, data calibration and verification of satellite altimeters, and other fields. The geophysical data record data of Jason-2 is used to extract and isolate the Ku-band σ 0 data of the Tibetan Plateau (TP). Methods: Taking the GlobeLand30 2020 version data as the basis for surface classification, σ 0 is given surface attributes by latitude and longi‑ tude data. And we obtain the time-varying sequences of σ 0 under different types of surface features from De‑ cember 2008 to September 2016. The singular spectrum analysis principle is used to extract the σ 0 time change trend and period information, and the period results are analyzed by fast Fourier transform. Results: The results show that the σ 0 is higher in waters and wetland areas, and is lower in permanent snow and ice areas. There are multiple period signals of σ 0 in the TP. Conclusions: The surface properties of the artificial surfaces, bare land, and shrubland area are stable, and the annual σ 0 change is not significant. The other re‑ gions have significant annual and semi-annual cycles of σ 0 variability, and the amplitude of variability is not consistent across regions, with different regions corresponding to different changes in σ 0 trends. [ABSTRACT FROM AUTHOR]

The water level of coastal wetlands is essential to the growth of mangroves in the development of the local economy. The current monitoring system still relies on hydrological stations to obtain the regular water level at fixed positions. However, the high costs of the conventional method cannot meet the harsh requirements in time. Satellite altimetry technology can be widely expected to serve as an effective supplement to ground monitoring. Taking the coastal wetland of Beibu Gulf in Guangxi as the research object, this study aims to propose a feasible monitoring technology for the water level using the daily Jason-3 and Sentinel-3A altimetry data from 2016 to 2020. The initial value of water level was calculated in coastal wetland through the radar altimetry toolbox, where the triple middle error was used to remove the outliers. The obtained initial points of the water level in the coastal wetland were first imported into the Omap, thereby removing the redundancy data of water level falling on the land and vegetation coverage. As such, high accuracy was achieved to prevent the waveforms near shore from the land. Four re-tracking were then used to correct the water level in the height measurement, including the shift of gravity center, threshold value, the improved shift of gravity center, and the improved threshold value. The determination coefficient, the Root Mean Square Error (RMSE), and the Mean Absolute Error (MAE) were selected to quantitatively evaluate the accuracy of two altimetry satellites. High-precision altimetry satellites were selected to explore the intra-year and inter-annual dynamic changes of water level in the coastal wetland at the intra-year, monthly, seasonal, and annual average water level. The results showed that the best re-setting effect was achieved in the improved threshold for the water level of coastal wetlands. By Jason-3A, the maximum determination coefficient was 0.78, the minimum RMSE was 0.35 m, and the minimum MAE was 0.28. By Sentinel-3A, the maximum determination coefficient was 0.87, the minimum RMSE was 0.24 m, and the minimum MAE was 0.18 m. It inferred that the high monitoring accuracy was obtained by Sentinel-3A. There was also obvious seasonality for the water level change of the coastal wetland in Beibu Gulf from 2016 to 2020. The average change of the water level was 3.37 m during the year. There was a drastic downward trend in the water level changes as a whole, with an average annual change rate of 0.005 m/a. The spaceborne radar altimeter provides a powerful method for monitoring the water level of coastal wetlands on a large scale, which is of great significance to the study of coastal wetland changes and ecological environment protection. [ABSTRACT FROM AUTHOR]

A long time series of the Ayakekumu Lake level change has been compiled by combination of the T/P, RA-2 and Hydroweb data. In addition, we assessed changing index of the Ayakekumu Lake during 1995-2015 based on Landsat images. The results showed that, the Ayakekumu Lake area and level increased continuously during the observation period, the area of lake increased from 624 km2 in 1995 to 995 km2 in 2015, and water level increased by 5 m in total in the period of 1995- 2015. Meanwhile, the air temperature had risen, and the area of glaciers retreated from 361.27 km2 in 1994 to 345.26 km2 in 2016. We concluded that the water volume change was related with climate factors, and the main factor was warm-wet climate. Additionally, atmosphere warning led to water level increase due to glaciers melting. The water volume changing in Ayakekumu Lake could be affected by the increasing precipitation as well as dropping evaporation. Some factors are likely to affect lake expansion, including permafrost melting and precipitation at high altitudes. In sum, accurate measurements of lake ice and water levels are critical for understanding the water resource balance and hydrologic cycle in arid or semi-arid regions of China. [ABSTRACT FROM AUTHOR]

The data of sensor geophysical data record(SGDR) of Jason-2 altimeter was collected in China coastal region, and four parameters maximum likelihood estimation method was used for waveform retracking, which can be applied for determinating the mean sea surface.The high frequency correction signals between adjacent observations along the track direction of the altimetry satellite Jason-2 SGDR(sensor geophysical data) record data are correlated near the offshore region. Based on this character, the method for optimal selection Gaussian low pass filter radius is put forward. Firstly, difference calculation is needed between the adjacent observations along the track direction. Secondly, form diffe-rence sequence data sets. Thirdly, determinate the filter radius according to correlation coefficient of the sequences. If the user wants to filter the SGDR data, it is best to select the filter radius of the Gaussian filter equals to 2 km. This method not only can suppress the high frequency error in the SSH(sea surface height), but also can ensure that the data is not excessively smooth. It can be considered as a reference for the establishment of high precision sea surface height model by making full use of satellite altimetry data in offshore region, and also can promote the construction of high precision sea seamless vertical datum. [ABSTRACT FROM AUTHOR]