Mass balances of individual glaciers on ice sheets have been previously reported by forming a mass budget of discharged ice and modelled ice sheet surface mass balance or a complementary method which measures volume changes over the glaciated area that are subsequently converted to glacier mass change. On ice sheets, volume changes have been measured predominantly with radar and laser altimeters but InSAR DEM differencing has also been applied on smaller ice bodies. Here, we report for the first time on the synergistic use of volumetric measurements from the CryoSat-2 radar altimetry mission together with TanDEM-X DEM differencing and calculate the mass balance of the two major outlet glaciers of the Northeast Greenland Ice Stream: Zachariæ Isstrøm and Nioghalvfjerdsfjorden (79North). The glaciers lost 3.59 ± 1.15 G t a − 1 and 1.01 ± 0.95 G t a − 1 , respectively, between January 2011 and January 2014. Additionally, there has been substantial sub-aqueous mass loss on Zachariæ Isstrøm of more than 11 G t a − 1 . We attribute the mass changes on both glaciers to dynamic downwasting. The presented methodology now permits using TanDEM-X bistatic InSAR data in the context of geodetic mass balance investigations for large ice sheet outlet glaciers. In the future, this will allow monitoring the mass changes of dynamic outlet glaciers with high spatial resolution while the superior vertical accuracy of CryoSat-2 can be used for the vast accumulation zones in the ice sheet interior.

Over the last decades the Greenland Ice Sheet (GrIS) has undergone a substantial shrinking of its mass. The mass loss is dominated by an accelerating discharge of outlet glaciers in south-east, west, and north-west Greenland (Khan et al., 2015). After glaciers in north-east Greenland had a longer period of relative stability they have shown an increase in dynamic thinning (Khan et al., 2014) and surface melt water runoff (Noël et al., 2019) since the early 2000s. To deal with this area in detail one has to take a closer look at the North-East Greenland Ice Stream (NEGIS). Accounting for about 16% of the entire area of the ice sheet (Khan et al., 2014), NEGIS originates near the summit and splits into the three main branches, Nioghalvfjerdsbrae (NG), Zachariae Isstrøm (ZI), and Storstrømmen (SN) (Figure 1). At present, the mass loss of the GrIS equals about 0.7 mm yr −1 of global sea-level rise (Forsberg et al., 2017;Shepherd et al., 2019; WCRP Global Sea Level Budget Group, 2018). The share of NG and ZI contribute less than 5% to this rise (Mouginot et al., 2019). However, in the consequence of ocean warming (Schaffer et al., 2020) the front of ZI will likely retreat another 30 km over the next decades and if, moreover, frontal melt rates exceed 6 m d −1 , ZI alone might contribute 16 mm to global mean sea level by 2,100 (Choi et al., 2017). Hence, it is essential to monitor ice-surface elevation and mass balance in order to detect and understand any substantial changes.Three main approaches are commonly used in order to infer the mass balance of ice sheets, namely the massbudget method, the gravity-change approach and the altimetry method. Results of the three methods were recently intercompared by Shepherd et al. (2019) andBamber et al. (2018). However, the majority of previous studies applied each method separately (e.g., for satellite altimetry: Hurkmans et al., 2014;

Satellite altimetry has been widely used to determine surface elevation changes in polar ice sheets. The original height measurements are irregularly distributed in space and time. Gridded surface elevation changes are commonly derived by repeat altimetry analysis (RAA) and subsequent spatial interpolation of height change estimates. This article assesses how methodological choices related to those two steps affect the accuracy of surface elevation changes, and how well this accuracy is represented by formal uncertainties. In a simulation environment resembling CryoSat-2 measurements acquired over a region in northeast Greenland between December 2010 and January 2014, different local topography modeling approaches and different cell sizes for RAA, and four interpolation approaches are tested. Among the simulated cases, the choice of either favorable or unfavorable RAA affects the accuracy of results by about a factor of 6, and the different accuracy levels are propagated into the results of interpolation. For RAA, correcting local topography by an external digital elevation model (DEM) is best, if a very precise DEM is available, which is not always the case. Yet the best DEM-independent local topography correction (nine-parameter model within a 3,000 m diameter cell) is comparable to the use of a perfect DEM, which exactly represents the ice sheet topography, on the same B Undine Strößenreuther