Regional Acceleration of the Antarctic Dynamic Ice Loss from Satellite Gravimetry

Theresa Diener,Ingo Sasgen

crossref(2022)

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摘要
<p>As large-scale circulation patterns change in the Southern Hemisphere the Antarctic ice sheet is exposed to increases in atmospheric and ocean temperatures. These climatological changes vary regionally and hold the potential to initiate processes that lead to ice sheet disintegration and sea level rise. In the Amundsen Sea region, in West Antarctica, major ice mass losses and increased ice flow can already be observed at present. Such processes are less common in East Antarctica but are also occurring in a more regionally restricted manner, for example to the glaciers feeding the Amery Ice Shelf.</p><p>The current state of the ice sheet is critical to evaluate the associated contribution to future global sea level rise. Therefore, we aim to quantify ice dynamic acceleration in Antarctica based on differencing GRACE/GRACE-FO and ERA5-SMB for the period 2002 to 2020. This indirect method provides an alternative to estimates that quantify ice stream acceleration based on satellite observations of surface ice velocity and is justified by the excellent agreement between GRACE/GRACE-FO and SMB on interannual time scales. In agreement with direct observations, our estimate identifies the Amundsen Sea embayment and the Bellingshausen Sea region in West Antarctica as the dominant source of dynamic loss and potential instability. We find that uncertainties in the SMB estimate are the dominant limitation in the accuracy of our outflow estimate. The uncertainties in our estimate can be reduced by further improvement of regional climate models. In this presentation, we introduce an alternative method to estimate dynamical acceleration, along with its uncertainty, and show its value in assessments of the state of the Antarctic ice sheet. We conclude that constraining the acceleration of ice sheet mass loss in the projection of sea level rise results in a contribution that is more than twice that of linear extrapolation to 2100.</p>
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