Collaborative Research: Combining Theory and Observations to Constrain Global Ocean Deoxygenation

合作研究：结合理论和观测来抑制全球海洋脱氧

• 批准号: 2229644
• 负责人: Curtis Deutsch
• 金额: $ 33.4万
• 依托单位: Princeton University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-04-01 至 2022-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2229644&HistoricalAwards=false
• 关键词: Collaborative; Research; Combining; Theory; Observations

This project will use a combination of ocean observations and modeling to understand why the dissolved oxygen concentration in the ocean changes on timescales of years to decades. As oceans absorb heat, its oxygen content is expected to decline which will affect marine ecosystems and oxygen-sensitive biochemical reactions. In turn, biochemical processes can affect the oxygen level. Understanding why oceanic oxygen changes remains limited due to sparse data and the fact that it naturally fluctuates. Furthermore, state-of-the-art Earth System Models, used to develop future projections, struggle to skillfully simulate present-day oxygen distributions. Given model biases, there is a clear need to re-calibrate model-based projections based on informed interpretations of available observations. The intellectual merit of this study is to perform a series of computational simulations to quantify linkages between the patterns of climate variability, ocean heating, and oxygen content for different regions. In conjunction with a novel synthesis of available observational data, this modeling study will develop a more comprehensive model for evaluating oxygen variability and change, thereby reducing uncertainty in future projections under climate forcing scenarios. Broader impacts of this study includes education and outreach about decreasing ocean concentrations in the ocean and its disruptive impacts on ocean biogeochemical cycles and marine ecosystems. Two Ph.D. students and a postdoctoral scientist will be trained under the supervision of the PIs. Ocean deoxygenation is a direct consequence of ocean heat uptake; as ocean waters warm, dissolved oxygen (O2) concentrations decline, with profound influences on marine ecosystem and redox-sensitive biogeochemical cycling. Existing observations are characterized by significant interannual to decadal fluctuations. Natural variability challenges detection and attribution of human-driven trends; however, it can also be interrogated to provide mechanistic insight. State-of-the-art Earth System Models still struggle to skillfully simulate present-day O2 distributions but these models are useful because they invoke mechanistic representations of key processes. The objective of this project is to improve our understanding of the mechanisms behind interannual and decadal variability of O2 globally and regionally. Low- and high-latitude regions exhibit distinct patterns in dissolved oxygen and ocean heat content. In order to isolate the impact of physical and biological controls on O2 variability, a suite of numerical simulations will be conducted, including some with a global eddy-resolving configuration. Combining observational and model-based analyses will enable quantitative assessments about the relation between ocean heat uptake and deoxygenation, and linkages to climate variability and trends.

该项目将结合海洋观测和建模，以了解为什么海洋中的溶解氧浓度在几年到几十年的时间尺度上发生变化。随着海洋吸收热量，其含氧量预计会下降，这将影响海洋生态系统和对氧敏感的生化反应。反过来，生物化学过程可以影响氧气水平。 了解为什么海洋氧气变化仍然有限，因为数据稀少，而且它自然波动。此外，用于开发未来预测的最先进的地球系统模型很难巧妙地模拟当今的氧气分布。鉴于模型存在偏差，显然需要根据对现有观测结果的知情解释，重新校准基于模型的预测。这项研究的智力价值是进行一系列的计算模拟，以量化不同地区的气候变率，海洋加热和氧含量模式之间的联系。结合对现有观测数据的新的综合，这项建模研究将开发一个更全面的模型，用于评估氧气的变异性和变化，从而减少气候强迫情景下未来预测的不确定性。这项研究的更广泛影响包括开展教育和宣传活动，使人们了解海洋中海洋浓度的降低及其对海洋生物地球化学循环和海洋生态系统的破坏性影响。两个博士学生和博士后科学家将在PI的监督下接受培训。海洋脱氧是海洋吸热的直接结果，随着海洋沃茨变暖，溶解氧（O2）浓度下降，对海洋生态系统和氧化还原敏感的海洋地球化学循环产生深远影响。现有观测的特点是显著的年际至十年波动。自然变异性对人类驱动趋势的检测和归因提出了挑战;然而，它也可以被询问以提供机械见解。最先进的地球系统模型仍然很难巧妙地模拟当今的O2分布，但这些模型是有用的，因为它们调用了关键过程的机械表示。该项目的目的是提高我们对全球和区域O2年际和年代际变化背后的机制的理解。低纬度和高纬度地区的溶解氧和海洋热含量呈现出不同的模式。为了隔离物理和生物控制对O2变异性的影响，将进行一系列数值模拟，包括一些具有全局涡流解析配置的数值模拟。将观测分析和基于模型的分析相结合，将能够对海洋吸热和脱氧之间的关系以及与气候变异性和趋势的联系进行定量评估。