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Earth structure beneath the Antarctic exerts an important control on the evolution of the ice sheet. A range of geological and geophysical data sets indicate that this structure is complex, with the western sector characterized by a lithosphere of thickness ∼50–100 km and viscosities within the upper mantle that vary by 2–3 orders of magnitude. Recent analyses of uplift rates estimated using Global Navigation Satellite System (GNSS) observations have inferred 1-D viscosity profiles below West Antarctica discretized into a small set of layers within the upper mantle using forward modelling of glacial isostatic adjustment (GIA). It remains unclear, however, what these 1-D viscosity models represent in an area with complex 3-D mantle structure, and over what geographic length-scale they are applicable. Here, we explore this issue by repeating the same modelling procedure but applied to synthetic uplift rates computed using a realistic model of 3-D viscoelastic Earth structure inferred from seismic tomographic imaging of the region, a finite volume treatment of GIA that captures this complexity, and a loading history of Antarctic ice mass changes inferred over the period 1992–2017. We find differences of up to an order of magnitude between the best-fitting 1-D inferences and regionally averaged depth profilesmore »through the 3-D viscosity field used to generate the synthetics. Additional calculations suggest that this level of disagreement is not systematically improved if one increases the number of observation sites adopted in the analysis. Moreover, the 1-D models inferred from such a procedure are non-unique, that is a broad range of viscosity profiles fit the synthetic uplift rates equally well as a consequence, in part, of correlations between the viscosity values within each layer. While the uplift rate at each GNSS site is sensitive to a unique subspace of the complex, 3-D viscosity field, additional analyses based on rates from subsets of proximal sites showed no consistent improvement in the level of bias in the 1-D inference. We also conclude that the broad, regional-scale uplift field generated with the 3-D model is poorly represented by a prediction based on the best-fitting 1-D Earth model. Future work analysing GNSS data should be extended to include horizontal rates and move towards inversions for 3-D structure that reflect the intrinsic 3-D resolving power of the data.

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Abstract The Patagonia Icefields (PIF) are the largest non-polar ice mass in the southern hemisphere. The icefields cover an area of approximately 16,500 km 2 and are divided into the northern and southern icefields, which are ~ 4000 km 2 and ~ 12,500 km 2 , respectively. While both icefields have been losing mass rapidly, their responsiveness to various climate drivers, such as the El Niño-Southern Oscillation, is not well understood. Using the elastic response of the earth to loading changes and continuous GPS data we separated and estimated ice mass changes observed during the strong El Niño that started in 2015 from the complex hydrological interactions occurring around the PIF. During this single event, our mass balance estimates show that the northern icefield lost ~ 28 Gt of mass while the southern icefield lost ~ 12 Gt. This is the largest ice loss event in the PIF observed to date using geodetic data.

Abstract Although modern global geometric reference frames (GRFs) such as the International Terrestrial Reference Frame (ITRF) can be used anywhere on Earth, regional reference frames (RRFs) are still used to densify geodetic control and optimize solutions for continental-scale areas and national purposes. Such RRFs can be formed by densifying the ITRF, utilizing GPS / GNSS stations common to both the ITRF and the RRF. It is possible to attach a RRF to a GRF by ensuring that some or all of the coefficients of the trajectory models in the RRF are ‘inherited’ from the trajectory models that define the GRF. This can be done on an epoch-by-epoch basis, or (our preference) via transformations that operate simultaneously in space and time. This paper documents inconsistencies in the densification of ITRF that arise when the common stations’ trajectory models ignore periodic displacements. This results in periodic coordinate biases in the RRF. We describe a generalized procedure to minimize this inconsistency when realizing any RRF aligned to the ITRF or any other ‘primary’ frame. We show the method used to realize the Argentine national frame Posiciones Geodésicas Argentinas (POSGAR) and discuss our results. Discrepancies in the periodic motion amplitudes in the vertical weremore »reduced from 4 mm to less than 1 mm for multiple stations after applying our technique. We also propose adopting object-oriented programming terminology to describe the relationship between different reference frames, such as a regional and a global frame. This terminology assists in describing and understanding the hierarchy in geodetic reference frames.« less

Abstract. Retreat and advance of ice sheets perturb the gravitational field, solidsurface and rotation of the Earth, leading to spatially variable sea-levelchanges over a range of timescales O(100−6 years), which in turn feedback onto ice-sheet dynamics. Coupled ice-sheet–sea-level models havebeen developed to capture the interactive processes between ice sheets, sealevel and the solid Earth, but it is computationally challenging to captureshort-term interactions O(100−2 years) precisely within longer O(103−6 years) simulations. The standard forward sea-level modelling algorithmassigns a uniform temporal resolution in the sea-level model, causing aquadratic increase in total CPU time with the total number of input icehistory steps, which increases with either the length or temporal resolutionof the simulation. In this study, we introduce a new “time window”algorithm for 1D pseudo-spectral sea-level models based on the normal modemethod that enables users to define the temporal resolution at which the iceloading history is captured during different time intervals before thecurrent simulation time. Utilizing the time window, we assign a finetemporal resolution O(100−2 years) for the period of ongoing andrecent history of surface ice and ocean loading changes and a coarsertemporal resolution O(103−6 years) for earlier periods in thesimulation. This reduces the total CPU time and memory required per modeltime stepmore »while maintaining the precision of the model results. We explorethe sensitivity of sea-level model results to the model temporal resolutionand show how this sensitivity feeds back onto ice-sheet dynamics in coupledmodelling. We apply the new algorithm to simulate sea-level changes inresponse to global ice-sheet evolution over two glacial cycles and the rapidcollapse of marine sectors of the West Antarctic Ice Sheet in the comingcenturies and provide appropriate time window profiles for each application.The time window algorithm reduces the total CPU time by ∼ 50 % in each of these examples and changes the trend of the total CPU timeincrease from quadratic to linear. This improvement would increase withlonger simulations than those considered here. Our algorithm also allows for couplingtime intervals of annual temporal scale for coupled ice-sheet–sea-levelmodelling of regions such as West Antarctica that are characterized byrapid solid Earth response to ice changes due to the thin lithosphere andlow mantle viscosities.« less

Abstract. Accurate glacial isostatic adjustment (GIA) modelling in the cryosphere is required for interpreting satellite, geophysical and geological recordsand for assessing the feedbacks of Earth deformation and sea-level change on marine ice-sheet grounding lines. GIA modelling in areas of active ice lossin West Antarctica is particularly challenging because the ice is underlain by laterally varying mantle viscosities that are up to several orders ofmagnitude lower than the global average, leading to a faster and more localised response of the solid Earth to ongoing and future ice-sheet retreatand necessitating GIA models that incorporate 3-D viscoelastic Earth structure. Improvements to GIA models allow for computation of the viscoelasticresponse of the Earth to surface ice loading at sub-kilometre resolution, and ice-sheet models and observational products now provide the inputs toGIA models at comparably unprecedented detail. However, the resolution required to accurately capture GIA in models remains poorly understood, andhigh-resolution calculations come at heavy computational expense. We adopt a 3-D GIA model with a range of Earth structure models based on recentseismic tomography and geodetic data to perform a comprehensive analysis of the influence of grid resolution on predictions of GIA in the AmundsenSea Embayment (ASE) in West Antarctica. Through idealised sensitivity testing downmore »to sub-kilometre resolution with spatially isolated ice loadingchanges, we find that a grid resolution of ∼ 13 of the radius of the load or higher is required to accurately capture the elasticresponse of the Earth. However, when we consider more realistic, spatially coherent ice loss scenarios based on modern observational records andfuture ice-sheet model projections and adopt a viscoelastic Earth, we find that predicted deformation and sea-level change along the grounding lineconverge to within 5 % with grid resolutions of 7.5 km or higher, and to within 2 % for grid resolutions of 3.75 km andhigher, even when the input ice model is on a 1 km grid. Furthermore, we show that low mantle viscosities beneath the ASE lead to viscousdeformation that contributes to the instrumental record on decadal timescales and equals or dominates over elastic effects by the end of the 21stcentury. Our findings suggest that for the range of resolutions of 1.9–15 km that we considered, the error due to adopting a coarser gridin this region is negligible compared to the effect of neglecting viscous effects and the uncertainty in the adopted mantle viscosity structure.« less