Simulating UNder ice Shelf Extreme Topography (SUNSET)

全球平均海平面正在以不断加快的速度上升。鉴于这一变化的巨大经济和社会影响，迫切需要准确的海平面预测，以告知决策者考虑减缓和适应战略。南极和格陵兰冰盖的融化目前造成了海平面上升的三分之一。这种融化的未来是高度不确定的，最坏的情况是冰盖对危险的海平面上升的巨大贡献。冰盖对海平面的最大贡献发生在海洋融化冰架底部（陆地冰盖的浮动延伸）时，增加了流入海洋的陆地冰。冰架的融化速度取决于海洋向冰的热量传递。最近，人们发现，在快速融化的冰架下面，极端的地形特征，包括台阶状的阶地和1-10公里宽的水道，无处不在。这些特征显著改变了融化的模式和速度，因此对预测海平面至关重要。然而，这些特征通常太小，无法在气候模式中解决，必须了解它们的影响并明确地纳入这些模式。我们将研究冰架底部的极端地形如何改变洋流和融化。在具有平滑、逐渐倾斜的底部的冰架下，融化可以被视为一个垂直过程，这就是目前气候模型中的表现方式。然而，观测表明，极端冰地形的陡峭斜坡上的融化实际上是水平的，比光滑冰底的融化快得多。此外，由极端地形特征产生的湍流海洋漩涡将向冰混合温暖的海水，进一步促进融化。我们将观察南极冰架下的极端冰地形的影响，使用加压热水钻穿超过一公里的冰，从而能够进入下面的海洋洞穴。我们将使用一套有针对性的最新观测测量来研究对融化的控制：雷达和声纳来跟踪冰的地形和融化，声学洋流剖面和一系列温度传感器来监测海洋热量向冰的混合。这将提供一个独特的海洋混合和冰融化之间的密切相互作用的数据集。然后，我们将结合联合收割机这些观测与计算机模拟的层次结构，开发一个新的代表性的极端冰地形的影响，在气候模式。我们将首先使用高分辨率的大涡模拟来模拟极端地形特征周围的流动，这种模拟可以解决海洋湍流问题。这将为了解温水与冰基的混合及其与融化的相互作用提供帮助。然后，我们将使用海洋模型来研究冰通道的几何形状对融化速率和流动特性的作用。利用这些模拟，我们将开发数学公式来表示极端冰地形的影响。我们将把这些公式应用到海洋模式中，并测试它在气候模式中代表极端冰地形影响的能力。

Global average sea level is rising at an ever-accelerating rate. Given the huge economic and societal impacts of this change, accurate forecasts of sea level are urgently needed to inform policymakers considering mitigation and adaptation strategies. Melting of the Antarctic and Greenland ice sheets currently contributes about one third of sea-level rise. The future of this melting is highly uncertain, and the worst-case scenario involves a substantial ice-sheet contribution to dangerous sea-level rise. The largest ice-sheet contribution to sea level occurs when the ocean melts the base of ice shelves (floating extensions of the grounded ice sheet), increasing the flow of grounded ice into the ocean. The melt rate of ice shelves is determined by the transfer of heat from the ocean towards the ice. Recently, extreme topographic features, including step-like terraces and 1-10 km wide channels, have been discovered to be ubiquitous on the underside of rapidly melting ice shelves. These features significantly modify the patterns and rates of melting, and so are crucial to predicting sea level. However, such features are generally too small to be resolved in climate models and their effect must be understood and explicitly built into these models. We will investigate how extreme topography on the underside of ice shelves changes ocean currents and melting. Beneath ice shelves with a smooth, gradually sloping base, melting can be viewed as a vertical process, and this is how it is currently represented in climate models. However, observations show that melting on the steeply sloping sides of extreme ice topography is actually horizontal, and much faster than the melting of a smooth ice base. In addition, turbulent ocean eddies generated by extreme topographic features will mix warm water up towards the ice, further enhancing the melting. We will observe the influence of extreme ice topography beneath an Antarctic ice shelf using pressurised hot water to drill through more than a kilometre of ice, enabling access to the ocean cavity beneath. We will study the controls on melting using a targeted suite of the latest observational measurements: radar and sonar to track the ice topography and melting, and acoustic ocean current profiling and a string of temperature sensors to monitor the mixing of ocean heat towards the ice. This will provide a unique dataset of the close interaction between ocean mixing and ice melting.We will then combine these observations with a hierarchy of computer simulations to develop a new representation of the effect of extreme ice topography in climate models. We will first simulate the flow around extreme topographic features using high-resolution large-eddy simulations, which resolve the ocean turbulence. This will provide insight into the mixing of warm water to the ice base, and its interaction with melting. We will then use an ocean model to study the role of ice channel geometry on the melt rate and flow properties. Using these simulations, we will develop mathematical formulae to represent the influence of extreme ice topography. We will implement these formulae into the ocean model and test its ability to represent the influence of extreme ice topography in climate models.