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.

[1] The accuracy of Global Positioning System (GPS) time series is degraded by the presence of offsets. To assess the effectiveness of methods that detect and remove these offsets, we designed and managed the Detection of Offsets in GPS Experiment. We simulated time series that mimicked realistic GPS data consisting of a velocity component, offsets, white and flicker noises (1/f spectrum noises) composed in an additive model. The data set was made available to the GPS analysis community without revealing the offsets, and several groups conducted blind tests with a range of detection approaches. The results show that, at present, manual methods (where offsets are hand picked) almost always give better results than automated or semi-automated methods (two automated methods give quite similar velocity bias as the best manual solutions). For instance, the fifth percentile range (5% to 95%) in velocity bias for automated approaches is equal to 4.2 mm/year (most commonly˙0.4 mm/yr from the truth), whereas it is equal to 1.8 mm/yr for the manual solutions (most commonly 0.2 mm/yr from the truth). The magnitude of offsets detectable by manual solutions is smaller than for automated solutions, with the smallest detectable offset for the best manual and automatic solutions equal to 5 mm and 8 mm, respectively. Assuming the simulated time series noise levels are representative of real GPS time series, robust geophysical interpretation of individual site velocities lower than 0.2-0.4 mm/yr is therefore certainly not robust, although a limit of nearer 1 mm/yr would be a more conservative choice. Further work to improve offset detection in GPS coordinates time series is required before we can routinely interpret sub-mm/yr velocities for single GPS stations.

[1] We describe how GPS time series are influenced by higher-order ionospheric effects over the last solar cycle (1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008) and examine implications for geophysical studies. Using 14 years of globally reprocessed solutions, we demonstrate the effect on the reference frame. Including second-and third-order ionospheric terms causes up to 10 mm difference in the smoothed transformation to the International Terrestrial Reference Frame (ITRF) 2005, with the Z translation term dominant. Scale is also slightly affected, with a change of up to ∼0.05 ppb. After transformation to ITRF2005, residual effects on vertical site velocities are as high as 0.34 mm yr −1 . We assess the effect of the magnetic field model on the second-order term and find a time-varying difference of 0-2 mm in the Z translation. We also assess the effect of omitting the third-order term. We find that while the second-order term is responsible for almost all the Z translation effects, it is the combination of the second-and third-order terms that causes the effect on scale. Comparison of our GPS reprocessing with ITRF2005 suggests that GPS origin rates may vary with time period. For example, we find Z translation rates of −0.82 ± 0.17 mm yr −1 for 1995-2008 and 0.17 ± 0.24 mm yr −1 for 1995-2005. If GPS were to contribute to origin rate definition for future ITRFs, higher-order ionospheric corrections would need to be applied due to their effect on translation parameters during solar maximum.

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