Climate of the LAst Millennium (CLAM): An Integrated Data-Model Approach to Reconstruct and Interpret Annual Variability in North Atlantic Circulation

北大西洋的海洋环流在控制区域和全球气候方面是多变的和关键的。这种变化既是自然发生的，也是预期的，是对人为活动的反应。到目前为止，这一系统的内部和强迫自然变异性在很大程度上表现在陆地档案和模型中，而不是在真正的海洋中。如果我们要正确地确定北大西洋环流中观察到的趋势，并制定强有力的早期预警系统，并计划适应未来的变化，我们就必须了解这种变化的规模、时间尺度、驱动因素和影响。在CLAM中，我们的目标是利用来自苏格兰西北部、冰岛北部和缅因湾的经过严格校准和核实的绝对年代学代理档案网络，以及高分辨率气候模型，来研究在过去1000年里驱动北大西洋环流模式变化的机制和作用力。这项提案是重新提交的(NE/M002160/1,2014年1月，等级8)，其中我们解决了审查员强调的小问题，特别是我们：(1)消除实地工作风险--利用独立资金完成所有必要的样本收集；(2)通过额外的初步模型-代理分析进一步展示方法的强大性质和潜在的调查结果；(3)通过与英国气象局哈德利中心发展更深层次的合作，产生更大的社会影响，以及(4)通过相关的成本节约，提高资金效益。

The ocean circulation of the North Atlantic is variable and pivotal in controlling regional and global climate. This variability occurs both naturally, and it is anticipated, in response to anthropogenic activity. Internal and forced natural variability in this system has so far largely been characterised in terrestrial archives and models rather than in the real ocean. It is critical that we understand the magnitude, timescale, drivers and impacts of this variability if we are to correctly attribute observed trends in the North Atlantic circulation, and develop robust early warning systems of, and plan adaptation to, future change. In CLAM we aim to utilise a network of robustly calibrated and verified absolutely dated sclerochronological proxy archives from NW Scotland, N. Iceland and the Gulf of Maine, together with high-resolution climate models, to investigate the mechanisms and forcings driving variability in the circulation patterns of the North Atlantic over the last millennium. This proposal is a resubmission (NE/M002160/1, Jan 2014, graded 8) in which we address minor concerns highlighted by the reviewers, notably we: (i) eliminate fieldwork risks - having completed all necessary sample collection using independent funding; (ii) further-demonstrate the powerful nature of the methodologies and potential findings though additional preliminary model-proxy analyses; (iii) greater societal impact via the development of a deeper collaboration with the Met Office Hadley Centre, and (iv) deliver improved value for money, through associated cost savings.