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The South China Sea is China's largest marginal sea area, and it is rich in oil and gas mineral resources; thus, estimating its sea level changes is of practical significance. Based on linear and nonlinear sea level change characteristics, this paper decomposes 1992–2019 monthly mean sea level anomaly time series in the South China Sea into trend, seasonal, and random terms. This paper compares the seasonal autoregressive integrated moving average (SARIMA) and Prophet models for estimating the trend and seasonal terms and the long short-term memory (LSTM) and radial basis function (RBF) models for estimating random terms, and the more suitable models were selected. A Prophet-LSTM combined model was developed based on the accuracy results. This paper uses the combined model to study the effect of known data length on the experimental results and determines the best prediction duration. The results show that the combined model is suitable for short-term and medium-term estimations of 12–36 months. The accuracy at 36 months is 0.962 cm, which proves that the combined model has high application value for estimating sea level changes in the South China Sea. [ABSTRACT FROM AUTHOR]

The Greenland ice sheet melting status is critical for global sea level rise and climate change. Based on the CryoSat-2 altimetry data from 2011 to 2021, the 5 km × 5 km DEMs of the Greenland ice sheet were derived by adopting the kriging interpolation method. Then the changes in elevation and volume of the ice sheet were calculated by using the intersection method. The changes in the ice sheet were analysed, and the results show that: (1) The accuracy of the Greenland DEMs obtained based on satellite altimetry data is region-dependent, with better accuracy in inland areas and higher elevation errors in marginal areas. (2) The inland area elevation remains unchanged basically or even shows an increasing trend, and there is an apparent melting trend in the marginal area, especially on the west coast. The contribution of the ice sheet melting mainly comes from elevations below 2000 m. (3) The main body of the Greenland ice sheet is melting with an elevation change rate of −13.27 ± 0.86 cm·a−1 and a volume change rate of −202.47 ± 14.8 km³·a−1. The rate of the Greenland ice sheet thinning has slowed down compared with the changes from 2003 to 2009. [ABSTRACT FROM AUTHOR]

In this paper, the Cryosat-2 altimeter data distributed by the ESA, and these data are processed to extract the information of the elevation change of the Antarctic ice sheet from 2010 to 2017.Firstly, the main pretreatment preprocessing for Cryosat-2 altimetry data is crossover adjustment and elimination of rough difference. Then the grid DEM of the Antarctic ice sheet was constructed by using the kriging interpolation method, and analyzed the spatial characteristic time characteristics of the Antarctic ice sheet. The latitude-weighted elevation can be obtained by using the elevation data of each cycle, and then the general trend of the Antarctic ice sheet elevation variation can be seen roughly. [ABSTRACT FROM AUTHOR]