Parameterizing the impact of fjord circulation on the ocean forcing of melting ice sheets

格陵兰冰盖的融化目前约占观测到的全球平均海平面上升的四分之一（在1992-2011年期间贡献了约7.5毫米），因此对全球受海平面变化影响的大部分人口产生了重大影响。格陵兰岛的冰融化也增加了流入北大西洋的淡水，有可能改变海洋环流，并对西北欧的气候产生重大影响。最先进的气候模型的预测包含了大气驱动的冰盖表面融化，但缺少海洋融化的成分。这种海洋融化发生在格陵兰岛周围冰川与海洋交汇的数百个峡湾。观测表明，区域海洋温度的年代际变化导致冰损失的显著变化。到达冰锋的温水加速了被淹没的冰川口和冰架的融化，导致内陆冰原区域的加速融化。从陆地进入海洋的冰通量的增加影响了海平面。由于峡湾的几何限制，海洋热量向冰的输送依赖于峡湾环流，其发生的尺度太小，无法用现代全球气候模式来表示。这种缺失过程的表示需要一种参数化方案，该方案由模拟的海洋属性驱动并影响其特性。缺乏这样的参数化是当代气候模型的一个严重限制：预计格陵兰岛周围的海洋未来会变暖，但我们无法准确预测对冰川融化和海平面上升的影响，因为我们缺乏解决这个问题所需的工具。因此，最近的IPCC报告一直在努力准确地估计这对海平面上升的贡献。该项目将开发和实施一个简单的冰川融化响应海洋强迫的参数化方法，该方法可用于在大尺度海洋和地球系统模型中表示小尺度峡湾过程。我们的团队将开发一个简化的模型，利用物理约束和流体动力学理论，捕捉峡湾和更广阔的海洋之间的热量和盐的交换率，以及它们对冰盖融化的影响。我们将在局部峡湾环境中使用高分辨率海洋模拟，并与格陵兰峡湾的持续测量结果进行比较，以校准该模型对一系列海洋条件和峡湾几何形状的响应。简化的模型将作为融化的参数化，可以应用于广泛的峡湾，我们将在英国气象局的海洋模型中实现这一点。最终的耦合模型将预测驱动冰盖模型和控制流入海洋的淡水流量的局部冰融化速率。我们的参数化将为英国气象局和全球其他气候模拟中心的气候和地球系统模型提供一种适应性强的工具。它将具有灵活的设计，提供基于当前知识的初步预测，但允许从未来的现场活动和建模研究中纳入新的限制，以解释新的过程。我们将加强对具有科学、技术、工程和数学（STEM）背景的学生的培训，并将他们的技能转化为应对环境挑战和解决英国关键技能差距的技能。我们将在牛津大学（Oxford University）接受环境研究核心知识和技能的强化培训，并在英国气象局（Met Office）获得高性能计算、代码开发和行业工作的实际经验。总之，我们密集的研究人员培训将为环境科学注入STEM技能，同时对海洋环流对格陵兰峡湾冰川融化的影响形成新的认识，并开发基于动态的这些影响的参数化，以用于未来的气候模式预测。

Melting of the Greenland ice sheet currently accounts for about a quarter of the observed global mean sea level rise (contributing approximately 7.5mm over the period 1992-2011), and therefore has significant impact on the large fraction of the global population who are influenced by changing sea level. Greenland ice melt is also increasing freshwater input to the North Atlantic, with the potential to alter ocean circulation and significantly influence the climate in north-west Europe. Predictions from state-of-the-art climate models incorporate the atmospherically-driven surface melt of ice sheets, but the component of marine melting is missing.This marine melting occurs in hundreds of fjords around Greenland where glaciers meet the ocean. Observations suggest that decadal variability in regional ocean temperature causes significant variability in ice loss. Warm water arriving at the ice front drives increased melting of submerged glacier snouts and ice shelves, leading to acceleration of inland regions of the ice sheet. The increased flux of ice from the land into the ocean impacts sea level.Due to the geometrical confinement in fjords, the transport of ocean heat towards the ice depends on fjord circulation occurring on scales too small to be represented in a modern global climate model. The representation of this missing process requires a parameterization scheme that is driven by and affects the modeled ocean properties. The lack of such a parameterization is a serious limitation of contemporary climate models: the oceans around Greenland are predicted to warm in the future, but we cannot accurately predict the impact on glacial melt and sea-level rise because we lack the tools required to address the problem. As a result, recent IPCC reports have struggled to accurately estimate this contribution to sea-level rise.This project will develop and implement a simple parameterization of glacial melt in response to ocean forcing, that can be used to represent small-scale fjord processes in large-scale ocean and earth system models. Our team will develop a simplified model to capture the exchange rates of heat and salt between a fjord and the wider ocean, and their impact on ice sheet melting, using physical constraints and fluid dynamics theory. We will calibrate the response of this model to a range of ocean conditions and fjord geometries, using high-resolution ocean simulations in a localized fjord setting and comparing to ongoing measurements in Greenland fjords. The simplified model will act as a parameterization of melting that can be applied to a wide range of fjords, and we will implement this in the Met Office ocean model. The final coupled model will predict local ice melt rates that drive an ice sheet model and control freshwater fluxes to the ocean.Our parameterization will provide an adaptable tool for immediate use in climate and Earth system models at the Met Office and other climate modelling centres worldwide. It will be of flexible design, providing initial predictions based on current knowledge, but allowing new constraints to be incorporated from future field campaigns and modeling studies that account for new processes.We will enhance the training of a student from a Science, Technology, Engineering & Mathematics (STEM) background, and translate their skills to tackle environmental challenges and address a key UK skills gap. We will dovetail intensive training at Oxford University on the core knowledge and skills for environmental research, with hands on experience of high performance computing, code development, and working in industry at the Met Office.In summary, our intensive researcher training will infuse STEM skills into environmental science, whilst simultaneously forging new understanding of the impact of ocean circulation on glacial melting in Greenland fjords, and developing a dynamically-based parameterization of these effects for use in future climate model projections.