Abstract
We present spatiotemporal mass balance trends for the Antarctic Ice Sheet from a statistical inversion of satellite altimetry, gravimetry, and elastic‐corrected GPS data for the period 2003–2013. Our method simultaneously determines annual trends in ice dynamics, surface mass balance anomalies, and a time‐invariant solution for glacio‐isostatic adjustment while remaining largely independent of forward models. We establish that over the period 2003–2013, Antarctica has been losing mass at a rate of −84 ± 22 Gt yr−1, with a sustained negative mean trend of dynamic imbalance of −111 ± 13 Gt yr−1. West Antarctica is the largest contributor with −112 ± 10 Gt yr−1, mainly triggered by high thinning rates of glaciers draining into the Amundsen Sea Embayment. The Antarctic Peninsula has experienced a dramatic increase in mass loss in the last decade, with a mean rate of −28 ± 7 Gt yr−1 and significantly higher values for the most recent years following the destabilization of the Southern Antarctic Peninsula around 2010. The total mass loss is partly compensated by a significant mass gain of 56 ± 18 Gt yr−1 in East Antarctica due to a positive trend of surface mass balance anomalies.
Highlights
Antarctica has been losing mass over the last two decades, probably at an accelerating rate [Williams et al, 2014; Harig and Simons, 2015]
The Antarctic mass balance is characterized by strong losses from the West Antarctic Ice Sheet (WAIS) and the Antarctic Peninsula (AP) with trends of −112 ± 12 Gt yr−1 and −28 ± 7 Gt yr−1, respectively, and a significant net mass gain trend of 56 ± 18 Gt yr−1 for the East Antarctic Ice Sheet (EAIS)
One of the strengths of our approach is that it allows us to assess the role of the physical processes (SMB and ice dynamics) in the overall mass balance, per drainage basin and per year
Summary
Antarctica has been losing mass over the last two decades, probably at an accelerating rate [Williams et al, 2014; Harig and Simons, 2015]. Three approaches are most commonly used: (i) estimating volume changes using satellite altimetry [e.g., Zwally et al, 2005] and converting these to a mass change, (ii) the input-output method (IOM) [e.g., Rignot et al, 2008] that compares ice discharge across (usually) the grounding line with snow accumulation over the upstream catchment area, and (iii) conversion of gravity anomalies from the Gravity Recovery and Climate Experiment (GRACE) satellites into mass trends All of these methods rely on forward models to solve for an unmeasured or unknown process that influences the observation. Simple arithmetic means of the combined estimates [Shepherd et al, 2012] mask the large differences between
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