PostDoctoral Research Fellowship

Goldberg/1103375该奖项支持博士后研究人员开发建模策略，以帮助解决未来几个世纪未来海平面上升(SLR)的最大不确定性来源之一，即西南极冰盖(WAIS)的贡献。目前的冰盖模型不足以减少这种不确定性，因为它的流动的许多决定因素很难或不可能直接观察到。此外，没有适当地评估冰的内部状态的影响，需要确定与WAIS当前状态有关的不确定性，并改进目前的数据同化技术。该奖项支持的博士后研究人员将使用一种新的大规模热机械冰模型，能够对WAIS进行建模，并将使用自动微分技术和分析方法在模型中加入一个伴随项。该辅助项将用于回答有关内部冰温和海洋强迫对WAIS演化的相对影响的问题，并利用卫星数据推断与时间相关的基本行为(这是目前尚未完成的工作)。主办科学家将是麻省理工学院的帕特里克·海姆巴赫博士，他在气候模型中伴随项的生成和使用方面的开创性工作将是无价的。这项拟议工作的学术价值在于，与时间相关的冰模型的伴随项的出现，有望改善数据同化和我们对冰盖动力学的理解。拟议工作的更广泛影响是量化未来陆冰对SLR贡献的最大不确定来源，这可以为政策决策提供信息，并指导未来的实地工作活动。

Goldberg/1103375This award supports a postdoctoral fellowship to develop a modeling strategy to help address one of the largest sources of uncertainty regarding future sea-level rise (SLR) over the next several centuries that of the contribution of the West Antarctic ice sheet (WAIS). Current ice sheet models are ill equipped to reduce this uncertainty because many of the determining factors of its flow are difficult or impossible to observe directly. In addition the influence of the internal state of the ice is not properly assessed and there is a need to characterize the uncertainty associated with the current state of WAIS, and to improve current data assimilation techniques. This post-doctoral researcher supported by this award will use a new large-scale thermo-mechanical ice model, capable of modeling WAIS and will incorporate an adjoint to the model using automatic differentiation techniques together with analytic methods. The adjoint will be used to answer questions regarding the relative influence of internal ice temperature and oceanic forcing on WAIS evolution, and to infer time-dependent basal behavior using satellite data (something not currently done). The host scientist will be Dr. Patrick Heimbach of MIT, whose pioneering work in the generation and use of adjoints in climate modeling will be invaluable. The intellectual merit of the proposed work is the advent of adjoints to time-dependent ice models, which promises improvements in data assimilation and in our understanding of ice sheet dynamics. The broader impact of the proposed work is quantification of the largest sources of uncertainty of future contributions of land ice to SLR, which could inform policy decisions and guide future fieldwork campaigns.