Marine Ice Sheet Instability Amplifies and Skews Uncertainty in Projections of Future Sea Level Rise

Marine Ice Sheet Instability Amplifies and Skews Uncertainty in Projections of Future Sea Level Rise
复制标题

海洋冰盖的不稳定加剧并扭曲了未来海平面上升预测的不确定性

DOI:
10.1073/pnas.1904822116
复制
发表时间:
2019
影响因子:
11.1
通讯作者:
Robel, A.A.. H.
Robel, A.A.. H.
中科院分区:
综合性期刊1区
文献类型:
--
作者:
Robel, A.A.. H.

文献摘要

相似文献

如果海洋冰盖变得不稳定,海平面上升可能会大大加速。如果出现这种不稳定性,由于模拟冰盖过程的不完善和不可预测的气候变化,未来海平面上升预测将存在相当大的不确定性。在这项研究中,我们使用数学和计算方法来确定冰盖的过程,驱动海平面预测的不确定性。使用随机扰动理论从统计物理学作为一种工具,我们在数学上表明,海洋冰盖的不稳定性大大放大和扭曲的不确定性,在海平面预测与最坏的情况下,海平面快速上升的可能性比最好的情况下,海平面上升较慢。我们还执行大型合奏模拟与国家的最先进的冰盖模型的Thwaites冰川,海洋终止冰川在南极洲西部,被认为是不稳定的。这些集合模拟表明,仅与内部气候变率有关的不确定性可能是思韦茨冰川预计的总冰损失的很大一部分。我们的结论是,内部气候变率可以单独负责海平面上升的预测显着的不确定性,大型合奏是量化这种不确定性的上限的必要工具。
Sea-level rise may accelerate significantly if marine ice sheets become unstable. If such instability occurs, there would be considerable uncertainty in future sea-level rise projections due to imperfectly modeled ice sheet processes and unpredictable climate variability. In this study, we use mathematical and computational approaches to identify the ice sheet processes that drive uncertainty in sea-level projections. Using stochastic perturbation theory from statistical physics as a tool, we show mathematically that the marine ice sheet instability greatly amplifies and skews uncertainty in sea-level projections with worst-case scenarios of rapid sea-level rise being more likely than best-case scenarios of slower sea-level rise. We also perform large ensemble simulations with a state-of-the-art ice sheet model of Thwaites Glacier, a marine-terminating glacier in West Antarctica that is thought to be unstable. These ensemble simulations indicate that the uncertainty solely related to internal climate variability can be a large fraction of the total ice loss expected from Thwaites Glacier. We conclude that internal climate variability alone can be responsible for significant uncertainty in projections of sea-level rise and that large ensembles are a necessary tool for quantifying the upper bounds of this uncertainty.