We use satellite and airborne altimetry to estimate annual mass changes of the Greenland Ice Sheet. We estimate ice loss corresponding to a sea-level rise of 6.9±0.4 millimeters from April 2011 to April 2020, with the highest annual ice loss rate of 1.4 mm/yr sea-level equivalent from April 2019 to April 2020. On a regional scale, our annual mass loss timeseries reveals 10-15 m/yr dynamic thickening at the terminus of Jakobshavn Isbræ from April 2016 to April 2018, followed by a return to dynamic thinning. We observe contrasting patterns of mass loss acceleration in different basins across the ice sheet. Our gridded satellite altimetry data and surface mass balance (SMB), along with corrections due to firn compaction are available for download. Here, we provide: (1) Annual (April to April) elevation change rates of the Greenland Ice Sheet from April 2011 to April 2020 from CryoSat-2, ICESat-2 and NASA’s ATM flights. 1x1 km grid. (2) Annual (April to April) elevation change rates due to SMB anomalies. 1x1 km grid. (3) Ice-sheet wide annual corrections due to firn compaction.

Although a number of studies indicate the regional heterogeneity of the glacier elevation and mass changes in high-mountain Asia in the early 21st century, little is known about these changes with high spatial detail for some of the regions. In this study we present respective glacier elevation and mass change estimates in the Indian state of Jammu and Kashmir (JK) for the period 2000–2012. Our estimates are based on the interferometric analysis of SRTM DEM and the bistatic TanDEM-X data. On an average the JK East (Karakoram) glaciers showed less negative elevation changes (− 0.19 ± 0.22 m/ yr) compared to the JK West (Himalaya) glaciers (− 0.50 ± 0.28m/yr). This agrees very well with previous studies that show a transition from larger changes in the western Himalaya to a steady-state situation in the Karakoram. We observe distinct elevation change patterns on a glacier scale that is most likely linked to debris insulation and the enhanced ice melting due to supraglacial lakes, ponds and ice cliffs. We also found 16 surge-type glaciers in the JK East which were not documented before. In total, 25 glaciers surged and 4 others appeared to be in a quiescent phase in the observation period. Our results also reveal that the glacier-averaged elevation change rates of surge-type and non surge-type glaciers in the JK East region are not significantly different.

Seasonal glacier ice velocities are important for precisely estimating annual ice discharge and understanding controlling mechanisms, but these measurements for a large number of Greenlandic glaciers are limited by low temporal resolution. We present seasonal changes in ice velocities, radar backscatter to mark the onset and extent of melt season and ice front positions of 45 Greenlandic glaciers using Sentinel-1 SAR data for the period 2015-2017. Seasonal velocity fluctuations of roughly half of the glaciers appear to be primarily controlled by surface-melt induced changes in the subglacial hydrology. This includes glaciers that speedup with the onset of surface melt and glaciers with comparable late winter and early melt season velocities showing significant slowdown during most of the melt season and speedup winter. Nearly 25% glaciers show strong correspondence between ice speed and terminus changes. Our results pinpoint the seasonal variations highlighting the variable influence of meltwater on year-around ice velocities.

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Previous studies have shown contrasting glacier elevation and mass changes in the sub-regions of high-mountain Asia. However, the elevation changes on an individual catchment scale can be potentially influenced by supraglacial debris, ponds, lakes and ice cliffs besides regionally driven factors. Here, we present a detailed study on elevation changes of glaciers in the Lahaul-Spiti region derived from TanDEM-X and SRTM C-/X-band DEMs during 2000-2012 and 2012-2013. We observe three elevation change patterns during 2000-2012 among glaciers with different extent of supraglacial debris. The first pattern (< 10 % debris cover, type-1) indicates maximum thinning rates at the glacier terminus and is observed for glacier with no or very low debris cover. In the second pattern (> 10 % debris cover, type-2), maximum thinning is observed up-glacier instead of glacier terminus. This is interpreted as the insulating effect of a thick debris cover. A third pattern, high elevation change rates near the terminus despite high debris cover (> 10 % debris cover, type-3) is most likely associated with either thinner debris thickness or enhanced melting at supraglacial ponds and lakes as well as ice cliffs. We empirically determined the SRTM C- and X-band penetration differences for debris-covered ice, clean ice/firn/snow and correct for this bias in our elevation change measurements. We show that this penetration bias, if uncorrected, underestimates the region-wide elevation change and geodetic mass balance by 20 %. After correction, the region-wide elevation change (1712 sqkm) was estimated to be -0.65±0.43 m/yr during 2000-2012. Due to the short observation period, elevation change measurements from TanDEM-X for selected glaciers in the period 2012-2013 are subject to large uncertainties. However, similar spatial patterns were observed during 2000-2012 and 2012-2013, but at different magnitudes. This study reveals that the thinning patterns of debris-covered glaciers cannot be generalized and spatially detailed mapping of glacier elevation change is required to better understand the impact of different surface types under changing climatic conditions.