Collaborative Research: Quantifying Abyssal Circulation and its Variability

1971年至2010年间，全球海洋吸收了超过90%的人为产生的多余热量，其中约10%进入深海，导致全球和局部海平面上升。尽管有这些广泛的社会影响，但推动深度变暖的机制仍然知之甚少。本项目旨在通过一项全球研究，利用化学示踪剂（在本例中为氟氯化碳；氟氯化碳）的新方法，克服以往由于数据稀疏限制而造成的障碍，从而提高我们对这些机制的理解。随着人为示踪剂进入并沿着海洋翻转环流的底部边缘循环，该分析将利用整个深海中可检测到的氯氟烃浓度的不断增长的数据集。该数据集既可以定义将新水引入深海的新途径，也可以评估深水形成速率的可变性。这种变率将考虑到与地表条件的相关性，从而评估驱动机制，从而将其纳入气候模式。此外，这项工作将在2021年项目结束前每年更新深海变暖、人为碳吸收和深海空间海平面上升的年代际趋势。研究结果将有助于确定当前的全球能源、碳和海平面收支，并促进我们对强迫人为热量和碳在整个海洋中分布的物理机制的理解。这项工作将证明和解释以前未知的用于气候模式的深度变率模式，从而改善二氧化碳排放增加下的长期气候预测，从而使社会更好地适应未来的变化。该项目将支持一名三年级研究生在SIO进行博士研究。此外，通过斯克里普斯海洋学研究所本科生研究奖学金（SURF）计划，将为本科生暑期学生提供较小的暑期项目。该项目将生成网格化的全球氯氟烃、深海变暖和海平面上升数据产品，这些数据产品将提供给更广泛的科学和教育界。本提案的总体目标是了解经向翻转环流（MOC）底部的变化，以便量化、解释和预测深海在海洋热量和碳吸收中的作用。深海正在以显著的速度变暖，这对海平面上升和海洋热吸收具有重要的气候影响。尽管有这些广泛的社会影响，但驱动这种深度变暖的机制仍然知之甚少，难以在气候模型中模拟，这降低了我们预测二氧化碳排放增加下气候将如何变化的能力。一种假设是，变暖是由南极洲周围深水形成的减少造成的。深海氯氟烃数据将通过模拟海洋地下响应并在其不确定性范围内拟合数据，用于在全球中性密度表面内制作年度网格图。网格化的CFC数据集将允许对深层环流、通风进行推断，并利用数十年的数据对任何地点的年代际变化进行评估。它将通过比较沿重复水文剖面的示踪剂年龄、氧气和深水体积的变化来验证观测到的任何年代际变化。将把年代际变率与观测到的深海变暖趋势进行比较，以确定这些变化是否导致了深海近期的热量积累，并探索驱动这种变率的任何机制。这项工作将有助于更好地描述沿MOC底部边缘的深海输送的平均值和变率，以及它是如何影响深海温度的。寻找含氯氟烃示踪剂运输的新方法，为深海环流、通风和变率提供了更好的估计，也将为未来监测全球深海变暖奠定基础。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The global ocean has absorbed over 90% of the excess anthropogenic heat between 1971 and 2010, with about 10% of that going into the deep ocean and contributing to global and local sea level rise. Despite these broad societal implications, the mechanisms driving the deep warming are still poorly understood. This project aims to improve our understanding of these mechanisms through a global study using a new method to utilize chemical tracers (in this case chlorofluorocarbons; CFCs) to overcome previous obstacles due to limitations from sparse data. The analysis will capitalize on a growing data set of detectable CFC concentrations throughout the deep ocean as anthropogenic tracers enter and circulate along the bottom limb of the overturning circulation of the ocean. This data set allows for both defining new pathways that bring new waters into the deep ocean and assessment of the variability in deep water formation rates. The variability will allow for correlations with surface conditions to evaluate driving mechanisms so that they can be included in climate models. In addition, this work will update decadal trends in abyssal warming, anthropogenic carbon uptake, and deep steric sea level rise annually through the end of the project in 2021. The results will help to close current global energy, carbon, and sea level budgets and advance our understanding of the physical mechanisms forcing the distribution of anthropogenic heat and carbon throughout the ocean. This work will demonstrate and explain modes of deep variability previously unknown for use in climate models leading to improved long-term climate projections under increased CO2 emissions, therefore enabling better societal adaptability to changes to come. The project will support a third year graduate student for his PhD work at SIO. In addition, smaller summer projects will be made available for undergraduate summer students through the Scripps Institution of Oceanography Undergraduates Research Fellowship (SURF) program. The project will produce gridded global CFC, deep ocean warming, and steric sea level rise data products that will be made available to the broader scientific and educational communities.The overall objective of this proposal is to understand the variability in the bottom limb of the Meridional Overturning Circulation (MOC) in order to quantify, explain, and forecast the role that the deep ocean plays in ocean heat and carbon uptake. The deep ocean is warming at a significant rate with important climatic implications for sea level rise and ocean heat absorption. Despite these broad societal implications, the mechanism driving this deep warming is still poorly understood and difficult to simulate in climate models, decreasing our ability to predict how the climate will change under increased CO2 emissions . One hypothesis is the warming is driven by a decrease in deep water formation around Antarctica. The deep CFC data will be used to produce annual gridded maps within neutral density surfaces around the globe by modeling the oceanic subsurface response and fitting the data within its uncertainty. The gridded CFC dataset will allow for inference of deep circulation, ventilation, and assessment of any interdecadal change in locations with multiple decades of data. It will validate any observed interdecadal variability by comparing to changes in tracer age, oxygen, and volume of deep water along repeated hydrographic sections. The decadal variability will be compared to observed deep warming trends in order to identify if these changes are causing the recent accumulation of heat in the abyssal ocean and explore any mechanisms driving the variability. This work will allow better characterization of the mean and variability of the deep transport along the bottom limb of the MOC and how it has affected deep-ocean temperatures. The new method to find tracer transport from CFCs to provide an improved estimate of deep ocean circulation, ventilation, and variability will also lay the groundwork for future monitoring of global deep-ocean warming.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.