The Greenland Ice Sheet has been a major contributor to global sea-level rise in recent decades ^1,2, and it is expected to continue to be so ³. Although increases in glacier flow ^4–6 and surface melting ^7–9 have been driven by oceanic ^10–12 and atmospheric ^13,14 warming, the magnitude and trajectory of the ice sheet’s mass imbalance remain uncertain. Here we compare and combine 26 individual satellite measurements of changes in the ice sheet’s volume, flow and gravitational potential to produce a reconciled estimate of its mass balance. The ice sheet was close to a state of balance in the 1990s, but annual losses have risen since then, peaking at 345 ± 66 billion tonnes per year in 2011. In all, Greenland lost 3,902 ± 342 billion tonnes of ice between 1992 and 2018, causing the mean sea level to rise by 10.8 ± 0.9 millimetres. Using three regional climate models, we show that the reduced surface mass balance has driven 1,964 ± 565 billion tonnes (50.3 per cent) of the ice loss owing to increased meltwater runoff. The remaining 1,938 ± 541 billion tonnes (49.7 per cent) of ice loss was due to increased glacier dynamical imbalance, which rose from 46 ± 37 billion tonnes per year in the 1990s to 87 ± 25 billion tonnes per year since then. The total rate of ice loss slowed to 222 ± 30 billion tonnes per year between 2013 and 2017, on average, as atmospheric circulation favoured cooler conditions ¹⁵ and ocean temperatures fell at the terminus of Jakobshavn Isbræ ¹⁶. Cumulative ice losses from Greenland as a whole have been close to the rates predicted by the Intergovernmental Panel on Climate Change for their high-end climate warming scenario ¹⁷, which forecast an additional 70 to 130 millimetres of global sea-level rise by 2100 compared with their central estimate.

@en

We present a new approach to estimate time variations in J2. Those variations are represented as the sum of contributions from individual sources. This approach uses solely Gravity Recovery And Climate Experiment (GRACE) data and the geoid fingerprints of mass redistributions that take place both at the surface and in the interior of the solid Earth. The results agree remarkably well with those based on satellite laser ranging, while estimates of the sources explain the observed variations in J2. Seasonal variations are dominated by terrestrial water storage and by mass redistribution in the atmosphere and ocean. Trends, however, are primarily controlled by the Greenland and Antarctic ice sheets and by glacial isostatic adjustment. The positive trend from surface mass variations is larger than the negative trend due to glacial isostatic adjustment and leads to an overall rising trend during the GRACE period (2002–2017).@en

The Antarctic Ice Sheet is an important indicator of climate change and driver of sea-level rise. Here we combine satellite observations of its changing volume, flow and gravitational attraction with modelling of its surface mass balance to show that it lost 2,720 ± 1,390 billion tonnes of ice between 1992 and 2017, which corresponds to an increase in mean sea level of 7.6 ± 3.9 millimetres (errors are one standard deviation). Over this period, ocean-driven melting has caused rates of ice loss from West Antarctica to increase from 53 ± 29 billion to 159 ± 26 billion tonnes per year; ice-shelf collapse has increased the rate of ice loss from the Antarctic Peninsula from 7 ± 13 billion to 33 ± 16 billion tonnes per year. We find large variations in and among model estimates of surface mass balance and glacial isostatic adjustment for East Antarctica, with its average rate of mass gain over the period 1992-2017 (5 ± 46 billion tonnes per year) being the least certain.

@en

Global Glacial Isostatic Adjustment (GIA) processes are usually represented by numerical models that simultaneously solve for glacial evolution and Earth rheology, being mainly constrained by the geological evidences of local ice extent and global sea level, as well as geodetic observations of Earth rotation. In recent years, GPS and GRACE observations have often been used to improve those models, especially in the context of regional studies, where the largest effects of lateral heterogeneities in the Earth structure are expected. However, regional models are intrinsically limited when it comes to answering questions from global scale geodesy. Examples are the closure of the sea level budget, the explanation of observed changes in Earth rotation, and the determination of the origin of the Earth reference frame. Furthermore, the issue of the consistency of regional models with each other is typically ignored. We consider this as a drawback, since such a consistency may not only be considered as an additional constraint, but is also important if the regional models are to be integrated into a global one. Here, we present a global empirical model of present-day mass changes driven by GIA, solely based on GRACE data and on geoid fingerprints of regional GIA combined with surface mass redistribution. We will show how the use of observations from a single space-borne platform allows us to tackle the questions from global scale geodesy mentioned above, and at the same time obtain a self-consistent GIA model at regional scales. @en

Global Glacial Isostatic Adjustment (GIA) processes are usually represented by numerical models that simultaneously solve for glacial evolution and Earth rheology, being mainly constrained by the geological evidences of local ice extent and global sea level, as well as geodetic observations of Earth rotation. In recent years, GPS and GRACE observations have often been used to improve those models, especially in the context of regional studies, where the largest effects of lateral heterogeneities in the Earth structure are expected. However, regional models are intrinsically limited when it comes to answering questions from global scale geodesy. Examples are the closure of the sea level budget, the explanation of observed changes in Earth rotation, and the determination of the origin of the Earth reference frame. Furthermore, the issue of the consistency of regional models with each other is typically ignored. We consider this as a drawback, since such a consistency may not only be considered as an additional constraint, but is also important if the regional models are to be integrated into a global one. Here, we present a global empirical model of present-day mass changes driven by GIA, solely based on GRACE data and on geoid fingerprints of regional GIA combined with surface mass redistribution. We will show how the use of observations from a single space-borne platform allows us to tackle the questions from global scale geodesy mentioned above, and at the same time obtain a self-consistent GIA model at regional scales. @en

Uncertainty in the geocenter position and its subsequent motion affects positioning estimates on the surface of the Earth and downstream products such as site velocities, particularly the vertical component. The current version of the International Terrestrial Reference Frame, ITRF2014, derives its origin as the long-term averaged center of mass as sensed by satellite laser ranging (SLR), and by definition, it adopts only linear motion of the origin with uncertainty determined using a white noise process. We compare weekly SLR translations relative to the ITRF2014 origin, with network translations estimated from station displacements from surface mass transport models. We find that the proportion of variance explained in SLR translations by the model-derived translations is on average less than 10%. Time-correlated noise and nonlinear rates, particularly evident in the Y and Z components of the SLR translations with respect to the ITRF2014 origin, are not fully replicated by the model-derived translations. This suggests that translation-related uncertainties are underestimated when a white noise model is adopted and that substantial systematic errors remain in the data defining the ITRF origin. When using a white noise model, we find uncertainties in the rate of SLR X, Y, and Z translations of ±0.03, ±0.03, and ±0.06, respectively, increasing to ±0.13, ±0.17, and ±0.33 (mm/yr, 1 sigma) when a power law and white noise model is adopted.

@en

When operating the Large Hadron Collider (LHC) in Geneva, circumference changes of the main ring can be inferred from the timing measurements with accuracies down to 10 micron. The circumference changes have been shown to correlate with Earth tides and surface mass loading. In this light, the LHC, may provide valuable observational constraints on surface loading problems often encountered in geodesy. In this presentation, besides showing correlations with surface loading changes from hydrology, and the atmosphere as derived from GRACE, we explore the theoretical framework to determinalistically couple the LHC circumference changes to elastic surface loading variations in the region.@en