Ice losses from the Greenland and Antarctic ice sheets have accelerated since the 1990s, accounting for a significant increase in the global mean sea level. Here, we present a new 29-year record of ice sheet mass balance from 1992 to 2020 from the Ice Sheet Mass Balance Inter-comparison Exercise (IMBIE). We compare and combine 50 independent estimates of ice sheet mass balance derived from satellite observations of temporal changes in ice sheet flow, in ice sheet volume, and in Earth's gravity field. Between 1992 and 2020, the ice sheets contributed 21.0±1.9 mm to global mean sea level, with the rate of mass loss rising from 105 Gt yr ⁻¹ between 1992 and 1996 to 372 Gt yr ⁻¹ between 2016 and 2020. In Greenland, the rate of mass loss is 169±9 Gt yr ⁻¹ between 1992 and 2020, but there are large inter-annual variations in mass balance, with mass loss ranging from 86 Gt yr ⁻¹ in 2017 to 444 Gt yr ⁻¹ in 2019 due to large variability in surface mass balance. In Antarctica, ice losses continue to be dominated by mass loss from West Antarctica (82±9 Gt yr ⁻¹ ) and, to a lesser extent, from the Antarctic Peninsula (13±5 Gt yr ⁻¹ ). East Antarctica remains close to a state of balance, with a small gain of 3±15 Gt yr ⁻¹ , but is the most uncertain component of Antarctica's mass balance. The dataset is publicly available at https://doi.org/10.5285/77B64C55-7166-4A06-9DEF-2E400398E452 (IMBIE Team, 2021).

We developed a multi-mission satellite altimetry analysis over the Antarctic Ice Sheet which comprises Seasat, Geosat, ERS-1, ERS-2, Envisat, ICESat and CryoSat-2. After a consistent reprocessing and a stepwise calibration of the inter-mission offsets, we obtained monthly grids of multi-mission surface elevation change (SEC) with respect to the reference epoch 09/2010 (in the format of month/year) from 1978 to 2017. A validation with independent elevation changes from in situ and airborne observations as well as a comparison with a firn model proves that the different missions and observation modes have been successfully combined to a seamless multi-mission time series. For coastal East Antarctica, even Seasat and Geosat provide reliable information and, hence, allow for the analysis of four decades of elevation changes. The spatial and temporal resolution of our result allows for the identification of when and where significant changes in elevation occurred. These time series add detailed information to the evolution of surface elevation in such key regions as Pine Island Glacier, Totten Glacier, Dronning Maud Land or Lake Vostok. After applying a density mask, we calculated time series of mass changes and found that the Antarctic Ice Sheet north of 81.5^∘ S was losing mass at an average rate of $-\mathrm{85}\pm \mathrm{16}$ Gt yr⁻¹ between 1992 and 2017, which accelerated to $-\mathrm{137}\pm \mathrm{25}$ Gt yr⁻¹ after 2010.

Supraglacial liquid water at the margins of ice sheets has an important impact on the surface energy balance and can also influence the ice flow when supraglacial lakes drain to the bed. Optical imagery is able to monitor supraglacial lakes during the summer season. Here we developed an alternative method using polarimetric SAR from Sentinel-1 during 2017–2020 to distinguish between liquid water and other surface types at the margin of the Northeast Greenland Ice Stream. This allows the supraglacial hydrology to be monitored during the winter months too. We found that the majority of supraglacial lakes persist over winter. When comparing our results to optical data, we found significantly more water. Even during summer, many lakes are partly or fully covered by a lid of ice and snow. We used our classification results to automatically map the outlines of supraglacial lakes, create time series of water area for each lake, and hence detect drainage events. We even found several winter time drainages, which might have an important effect on ice flow. Our method has problems during the peak of the melt season, but for the rest of the year it provides crucial information for better understanding the component of supraglacial hydrology in the glaciological system.

Ice-surface elevation profiles of more than 30 000 km in total length are derived from kinematic GNSS (GPS and the Russian GLONASS) observations on sledge convoy vehicles along traverses between Vostok Station and the East Antarctic coast. These profiles have accuracies between 4 and 9 cm. They are used to validate elevation data sets from both radar and laser satellite altimetry as well as four digital elevation models. A crossover analysis with three different processing versions of Envisat radar altimetry elevation profiles yields a clear preference for the relocation method over the direct method of slope correction and for threshold retrackers over functional fit algorithms. The validation of CryoSat-2 low-resolution mode and SARIn mode data sets documents the progress made from baseline B to C elevation products. ICESat laser altimetry data are demonstrated to be accurate to a few decimetres over a wide range of surface slopes. A crossover adjustment in the region of subglacial Lake Vostok combining ICESat elevation data with our GNSS profiles yields a new set of ICESat laser campaign biases and provides new, independent evidence for the stability of the ice-surface elevation above the lake. The evaluation of the digital elevation models reveals the benefits of combining laser and radar altimetry.

Glacial isostatic adjustment (GIA) is a major source of uncertainty for ice and ocean mass balance estimates derived from satellite gravimetry. In Antarctica the gravimetric effect of cryospheric mass change and GIA are of the same order of magnitude. Inverse estimates from geodetic observations hold some promise for mass signal separation. Here, we investigate the combination of satellite gravimetry and altimetry and demonstrate that the choice of input data sets and processing methods will influence the resultant GIA inverse estimate. This includes the combination that spans the full GRACE record (April 2002–August 2016). Additionally, we show the variations that arise from combining the actual time series of the differing data sets. Using the inferred trends, we assess the spread of GIA solutions owing to (1) the choice of different degree-1 and C₂₀ products, (2) viable candidate surface-elevation-change products derived from different altimetry missions corresponding to different time intervals, and (3) the uncertainties associated with firn process models. Decomposing the total-mass signal into the ice mass and the GIA components is strongly dependent on properly correcting for an apparent bias in regions of small signal. Here our ab initio solutions force the mean GIA and GRACE trend over the low precipitation zone of East Antarctica to be zero. Without applying this bias correction, the overall spread of total-mass change and GIA-related mass change using differing degree-1 and C₂₀ products is 68 and 72 Gt a⁻¹, respectively, for the same time period (March 2003–October 2009). The bias correction method collapses this spread to 6 and 5 Gt a⁻¹, respectively. We characterize the firn process model uncertainty empirically by analysing differences between two alternative surface mass balance products. The differences propagate to a 10 Gt a⁻¹ spread in debiased GIA-related mass change estimates. The choice of the altimetry product poses the largest uncertainty on debiased mass change estimates. The spread of debiased GIA-related mass change amounts to 15 Gt a⁻¹ for the period from March 2003 to October 2009. We found a spread of 49 Gt a⁻¹ comparing results for the periods April 2002–August 2016 and July 2010–August 2016. Our findings point out limitations associated with data quality, data processing, and correction for apparent biases.

We present the results of glaciological investigations in the megadune area located 30 km to the east of Vostok Station (central East Antarctica) implemented during the 58th, 59th and 60th Russian Antarctic Expedition (January 2013–2015). Snow accumulation rate and isotope content (δD, δ¹⁸O and δ¹⁷O) were measured along the 2 km profile across the megadune ridge accompanied by precise GPS altitude measurements and ground penetrating radar (GPR) survey. It is shown that the spatial variability of snow accumulation and isotope content covaries with the surface slope. The accumulation rate regularly changes by 1 order of magnitude within the distance < 1 km, with the reduced accumulation at the leeward slope of the dune and increased accumulation in the hollow between the dunes. At the same time, the accumulation rate averaged over the length of a dune wave (22 mm w.e.) corresponds well with the value obtained at Vostok Station, which suggests no additional wind-driven snow sublimation in the megadunes compared to the surrounding plateau. The snow isotopic composition is in negative correlation with the snow accumulation. Analysing dxs ∕ δD and ¹⁷O-excess ∕ δD slopes (where dxs = δD − 8 ⋅ δ¹⁸O and ¹⁷O-excess = ln(δ¹⁷O ∕ 1000 + 1) −0.528 ⋅ ln (δ¹⁸O ∕ 1000 + 1)), we conclude that the spatial variability of the snow isotopic composition in the megadune area could be explained by post-depositional snow modifications. Using the GPR data, we estimated the apparent dune drift velocity (4.6 ± 1.1 m yr⁻¹). The full cycle of the dune drift is thus about 410 years. Since the spatial anomalies of snow accumulation and isotopic composition are supposed to drift with the dune, a core drilled in the megadune area would exhibit the non-climatic 410-year cycle of these two parameters. We simulated a vertical profile of snow isotopic composition with such a non-climatic variability, using the data on the dune size and velocity. This artificial profile is then compared with the real vertical profile of snow isotopic composition obtained from a core drilled in the megadune area. We note that the two profiles are very similar. The obtained results are discussed in terms of interpretation of data obtained from ice cores drilled beyond the megadune areas.