Abstract. The Antarctic Ice Sheet is the largest potential source of future sea-level rise. Mass loss has been increasing over the last two decades in the West Antarctic Ice Sheet (WAIS), but with significant discrepancies between estimates, especially for the Antarctic Peninsula. Most of these estimates utilise geophysical models to explicitly correct the observations for (unobserved) processes. Systematic errors in these models introduce biases in the results which are difficult to quantify. In this study, we provide a statistically rigorous, error-bounded trend estimate of ice mass loss over the WAIS from 2003–2009 which is almost entirely data-driven. Using altimetry, gravimetry, and GPS data in a hierarchical Bayesian framework, we derive spatial fields for ice mass change, surface mass balance, and glacial isostatic adjustment (GIA) without relying explicitly on forward models. The approach we use separates mass and height change contributions from different processes, reproducing spatial features found in, for example, regional climate and GIA forward models, and provides an independent estimate, which can be used to validate and test the models. In addition, full spatial error estimates are derived for each field. The mass loss estimates we obtain are smaller than some recent results, with a time-averaged mean rate of −76 ± 15 GT yr−1 for the WAIS and Antarctic Peninsula (AP), including the major Antarctic Islands. The GIA estimate compares very well with results obtained from recent forward models (IJ05-R2) and inversion methods (AGE-1). Due to its computational efficiency, the method is sufficiently scalable to include the whole of Antarctica, can be adapted for other ice sheets and can easily be adapted to assimilate data from other sources such as ice cores, accumulation radar data and other measurements that contain information about any of the processes that are solved for.
Neuromodulation Improves the Evolution of Forward Models
