Collaborative Research: Quantifying Abyssal Circulation and Its Variability

在1971年至2010年间，全球海洋吸收了超过90%的过量人为热量，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，但对驱动深度变暖的机制仍然知之甚少。该项目旨在通过一项全球性研究来提高我们对这些机制的理解，该研究使用一种新的方法来利用化学示踪剂（在这种情况下是氯氟烃; CFCs），以克服以前由于缺乏数据而造成的障碍。随着人为示踪物进入海洋翻转环流的底缘并沿其沿着循环，分析将利用整个深海可检测到的氟氯化碳浓度的不断增加的数据集。这一数据集既可确定将新的沃茨带入深海的新路径，又可评估深海水形成率的变化。这种变化将允许与地表条件的相关性，以评估驱动机制，从而将其纳入气候模型。此外，这项工作将更新深海变暖、人为碳吸收和深海空间海平面上升的十年趋势，直到2021年项目结束。这些结果将有助于关闭当前的全球能源，碳和海平面预算，并促进我们对迫使整个海洋人为热量和碳分布的物理机制的理解。这项工作将展示和解释以前未知的用于气候模型的深度变异模式，从而改善二氧化碳排放增加情况下的长期气候预测，从而使社会能够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攻读博士学位。此外，通过斯克里普斯海洋学研究所的本科生研究奖学金（SURF）计划，将为本科生暑期学生提供较小的暑期项目。该项目将制作网格化的全球CFC、深海变暖和空间海平面上升数据产品，提供给更广泛的科学和教育界，该提案的总体目标是了解经向翻转环流（MOC）底翼的变化，以便量化、解释和预测深海在海洋热量和碳吸收方面的作用。深海正在以显著的速度变暖，对海平面上升和海洋吸热产生重要的气候影响。 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后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所驱动的。 深层CFC数据将用于制作地球仪周围中性密度表面内的年度网格图，方法是模拟海洋次表层响应并在其不确定性范围内拟合数据。网格化的CFC数据集将允许推断深环流，通风，并评估具有数十年数据的位置的任何年代际变化。它将通过与示踪剂年龄、氧气和沿着重复水文剖面的深水体积的变化进行比较，验证任何观测到的年代际变化。将把十年变化与观测到的深海变暖趋势进行比较，以确定这些变化是否是造成深海最近热量积累的原因，并探讨造成这种变化的任何机制。 这项工作将有助于更好地说明主海洋活动中心底缘沿着深层迁移的平均值和变异性，以及它如何影响深海温度。寻找CFC示踪物传输的新方法，以提供对深海环流、通风和变化的更好估计，也将为未来监测全球深海变暖奠定基础。该奖项反映了NSF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.