The elevation changes of ice sheets have been recognized as an essential climate variable. Long-term time series of these changes are an important parameter to understand climate change, and the longest time-series of ice sheet elevation changes can be derived from combining multiple Ku-band satellite altimetry missions. However, unresolved intermission biases obscure the record. Here, we revise the mathematical model commonly used in the literature to simultaneously correct for intermission bias and ascending–descending bias to ensure the self-consistency and cohesion of the elevation time series across missions. This updated approach is applied to combine Envisat and CryoSat-2 radar altimetry in the period of 2002–2019. We tested this approach by validating it against airborne and satellite laser altimetry. Combining the detailed temporal and spatial evolution of elevation changes with firn densification-modeled volume changes due to surface processes, we found that the Amundsen Sea sector accounts for most of the total volume loss of the Antarctic Ice Sheet (AIS), mainly from ice dynamics. However, surface processes dominate the volume changes in the key regions, such as the Totten Glacier sector, Dronning Maud Land, Princess Elizabeth Land, and the Bellingshausen Sea sector. Overall, accelerated volume loss in the West Antarctic continues to outpace the gains observed in the East Antarctic. The total volume change during 2002–2019 for the AIS was −68.7 ± 8.1 km3/y, with an acceleration of −5.5 ± 0.9 km3/y2.
The waveform retracking algorithm is a key factor that affects the accuracy of elevation change from satellite altimetry over an ice sheet. The elevation change results from four waveform retracker algorithms (ICE1/ICE2/Sea Ice/OCEAN) provided by the Satellite with ARgos and ALtiKa (SARAL/ALtiKa) data were compared using repeated SARAL data between March 2013 and April 2016 to determine the optimal retracker in the crossovers of descending and ascending orbits over a Greenland ice sheet (GrIS). The ICE1 provided slightly better results than the three other algorithms with the lowest standard deviation (SD) of 0.30 m year−1. Further comparison was also conducted between the Satellite with ARgos and ALtiKa (SARAL) and Operation ICEBridge laser data, thereby indicating that ICE1 was the best retracker with an Root Mean Square Error (RMSE) of 0.43 m year−1. The distribution of elevation change rate and uncertainties over Greenland from SARAL were presented using the selected ICE1 retracker with a volume loss of 40 12 km3 year−1. This volume loss did not include the fast-changing coastal areas of the GrIS. A large thinning was observed in Jakobshavn Isbræ, and a trend that extended far inland was also found from 2013–2016. Furthermore, a melting ice sheet was observed in the large areas northwest over the GrIS.
Satellite altimetry is an important data source for ice sheet change observation. The long-term time series of ice sheet changes can be obtained by combining satellite altimetry missions with similar sensor characteristics. Then, how to correct the inter-mission offsets becomes an important scientific issue. Review of previous studies, we found that the observations of satellite ascending and descending orbits also have an important influence on the estimation of inter-mission offsets. On this basis, have created a new least-square fitting mathematical model to estimate and correct the errors of ascending and descending orbits and inter-mission offsets by introducing the inter-mission offsets terms related to the observations of ascending and descending orbits. Utilizing this model, we developed a time series of monthly Antarctic ice sheet elevation changes of 5 km grid from May 2002 to April 2019. A validation with surface elevation from airborne observations and a comparison with surface elevation changes from ICESat proved that the proposed model can successfully estimate and correct the errors and be used to construct multi-mission surface elevation time series. Without a doubt, the temporal and spatial changes of Antarctic ice sheet elevation can be obtained from our monthly grid time series. From the time series, we find that over the period May 2002 to April 2019 the loss of ice and snow in the Antarctic ice sheet mainly occurred in the glaciers along the Amundsen coast in the West Antarctic and the Totten glacier in the East Antarctic, while the accumulation took place in Queen Maud of the East Antarctic. In May 2002, the Antarctic ice sheet experienced a volume loss of -71.4 ± 11.7 km3/yr, with an acceleration of –5.8 ± 1.2 km3/yr2 over the period May 2002 to April 2019, including 45.0 ± 9.6 km3/yr and 0.1 ±1.0 km3/yr2 for the East Antarctic ice sheet, -97.0 ± 4.4 km3/yr and -7.6 ±0.5 km3/yr2 for the West Antarctic ice sheet and -19.5 ± 5.3 km3/yr and 1.7 ±0.5 km3/yr2 for the Antarctic Peninsula ice sheet.