Understanding Interdecadal Changes in the Ocean Carbon Sink (UNICORNS)

了解海洋碳汇的年代际变化（UNICORNS）

• 批准号: NE/W001543/1
• 负责人: Andrew Watson
• 金额: $ 80.87万
• 依托单位: UNIVERSITY OF EXETER
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FW001543%2F1
• 关键词: Understanding; Interdecadal; Changes; Ocean; Carbon

The oceans have absorbed more than a quarter of the carbon dioxide (CO2) that humans release to the atmosphere, a process that substantially slows the pace of climate change. However, this ocean "sink" for CO2 is not constant: observational estimates based on surface ocean measurements suggest it changed little through the 1990s, but after 2000 it began to increase rapidly. The reasons for this variability are not understood. Earth system models for the climate and carbon cycle do not capture the variation, indicating fundamental deficiencies in the models. This is a major problem because the models are our tools to project how the climate will change in the future. Changes in the physical circulation of the ocean, or its biogeochemistry, may be responsible for the observed variability - or perhaps sparse observations in earlier decades have biased observations and exaggerated the variability. In UNICORNS we will bring several newly developed techniques to resolve these questions. (1) We will apply several machine learning methods to observations of the ocean interior, to reconstruct the ocean carbon content in greater detail than previously possible. This will enable us to test whether the time history of the carbon inventory as revealed by the interior observations, is consistent with that deduced from surface measurements. This will provide an independent test of the apparent sink variability. (2) To examine possible ocean circulation mechanisms that could cause the variability, we will adapt and apply a novel "inverse" technique that constructs budgets for temperature and salinity within water masses. This can explicitly derive regional mixing and transport, changes that could lead to the variable carbon sink. (3) Much of the sink variability may be attributable to changes in circulation redistributing "natural" carbon that has been in the ocean since pre-industrial times. We will apply a framework that explicitly identifies added and redistributed carbon to model output to examine this hypothesis and to evaluate the results of our inverse method. Different techniques used in the literature define the split between "anthropogenic" and natural, pre-existing carbon, in different ways and with this part of our project we will aim to bring more clarity to this distinction.Our results will enable a more assured interpretation of the global carbon budget over recent decades, improvements to carbon-climate models, and more confident projections of future climate.

海洋吸收了人类释放到大气中的二氧化碳（CO2）的四分之一以上，这一过程大大减慢了气候变化的速度。但是，对于CO2而言，这种海洋“下沉”不是恒定的：基于表面海洋测量值的观察估计表明，它在1990年代的变化很小，但是2000年之后，它开始迅速增加。这种变异性的原因尚不清楚。气候和碳循环的地球系统模型不会捕获变化，表明模型中的基本缺陷。这是一个主要问题，因为这些模型是我们投影气候将来将如何变化的工具。海洋物理循环或其生物地球化学的变化可能导致观察到的可变性 - 或者可能在早期几十年中稀疏观察到了偏差的观察结果并夸大了变异性。在独角兽中，我们将带来几种新开发的技术来解决这些问题。 （1）我们将采用几种机器学习方法来观察海洋内部，以比以前更详细地重建海洋碳含量。这将使我们能够测试内部观察结果所揭示的碳库存的时间历史是否与从表面测量结果得出的时间历史一致。这将提供对明显下沉变异性的独立测试。 （2）检查可能导致可变性的可能的海洋循环机制，我们将适应并应用一种新颖的“反向”技术，该技术构建了水质量内温度和盐度的预算。这可以明确地得出区域混合和运输，这可能导致可变的碳汇。 （3）许多下水道的可变性可能归因于自工业前时代以来一直在海洋中重新分布“天然”碳的变化。我们将应用一个框架，该框架明确识别添加并重新分配的碳来模型输出，以检查该假设并评估我们的逆方法的结果。文献中使用的不同技术定义了“人类学”和自然，预先存在的碳，以不同的方式，在我们的项目的这一部分之间，我们的目标是对这种区别提高清晰度。我们的结果将使您的结果能够更加确保对全球碳预算进行更加确保的解释，在最近的几十年中，对碳气候模型的改进，改进了未来的碳气候模型，并更加自信地投影了未来的风光。