Reconciled estimation of Antarctic ice sheet mass balance and contribution to global sea level change from 1996 to 2021

Abstract

The Antarctic Ice Sheet (AIS) has been losing ice mass and contributing to global sea level rise (GSLR). Given its mass that is enough to cause ∼58 m of GSLR, accurate estimation of mass balance trend is critical for AIS mass loss monitoring and sea level rise forecasting. Here, we present an improved approach to reconciled solutions of mass balance in AIS and its regions from multiple contributing solutions using the input-out, altimetric, and gravimetric methods. In comparison to previous methods, such as IMBIE 2018, this approach utilizes an adaptive data aggregation window to handle the heterogeneity of the contributing solutions, including the number of solutions, temporal distributions, uncertainties, and estimation techniques. We improved the regression-based method by using a two-step procedure that establishes ensembled solutions within each method (input-output, altimetry, or gravimetry) and then estimates the method-independent reconciled solutions. For the first time, 16 contributing solutions from 8 Chinese institutions are used to estimate the reconciled mass balance of AIS and its regions from 1996 to 2021. Our results show that AIS has lost a total ice mass of ∼3213±253 Gt during the period, an equivalent of ∼8.9±0.7 mm of GSLR. There is a sustained mass loss acceleration since 2006, from 88.1±3.6 Gt yr −1 during 1996–2005 to 130.7±8.4 Gt yr −1 during 2006–2013 and further to 157.0±9.0 Gt yr −1 during 2014–2021. The mass loss signal in the West Antarctica and Antarctic Peninsula is dominant and clearly presented in the reconciled estimation and contributing solutions, regardless of estimation methods used and fluctuation of surface mass balance. Uncertainty and challenges remain in mass balance estimation in East Antarctica. This reconciled estimation approach can be extended and applied for improved mass balance estimation in the Greenland Ice Sheet and mountain glacier regions.

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