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.

海洋吸收了人类排放到大气中的二氧化碳（CO2）的四分之一以上，这一过程大大减缓了气候变化的速度。然而，海洋中的二氧化碳“汇”并不是恒定不变的：基于海洋表面测量的观测估计表明，在20世纪90年代，它几乎没有变化，但在2000年之后，它开始迅速增加。造成这种差异的原因尚不清楚。气候和碳循环的地球系统模型没有捕捉到这种变化，这表明模型存在根本性缺陷。这是一个主要问题，因为模型是我们预测未来气候变化的工具。海洋物理循环或海洋地球化学的变化可能是观测到的变异性的原因，也可能是前几十年的稀疏观测导致了观测结果的偏差，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)我们将应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测所揭示的碳清单的时间历史是否与从表面测量中推导出的一致。这将提供一个独立的测试表观汇的可变性。(2)为了研究可能导致变化的海洋环流机制，我们将采用并应用一种新的“逆”技术，该技术构建水团内温度和盐度的预算。这可以明确地得出区域混合和运输，变化可能导致可变的碳汇。(3)汇的变异性大部分可归因于循环的变化，重新分配自工业化前时代以来一直存在于海洋中的“天然”碳。我们将应用一个框架，明确识别增加和重新分配的碳模型输出来检验这一假设，并评估我们的逆方法的结果。文献中使用的不同技术以不同的方式定义了“人为”和自然的、预先存在的碳之间的分离，我们的项目的这一部分旨在更清晰地区分这种区别。我们的结果将使近几十年来全球碳预算的解释更有把握，碳气候模型的改进，以及对未来气候的更有信心的预测。