Collaborative Research: Using models and historical data to guide effective monitoring and enhance understanding of deep ocean oxygen variability

合作研究：利用模型和历史数据指导有效监测并增强对深海氧气变化的理解

• 批准号: 2242743
• 负责人: Helen Pillar
• 金额: $ 12.57万
• 依托单位: University of Texas at Austin
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-05-01 至 2026-04-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2242743&HistoricalAwards=false
• 关键词: Collaborative; Research; Using; models; historical

The ocean is home to larger lifeforms that need oxygen to breathe and smaller lifeforms that produce about half of the oxygen we end up breathing. Concerningly, the observational record indicates that the ocean is losing its oxygen content. State-of-the-art climate models predict this trend will continue through the end of the 21st century. Rates and cause of the oxygen loss are highly uncertain due to sparse data coverage. In recent years, we have learned greatly about the ocean’s salinity and temperature changes from measurements made by the fleet of profiling floats of the Argo program. To date, most of these floats have not measured oxygen. Proposed expansions of the Biogeochemical (operating over the upper 2000 m) and Deep (4000 to 6000 m) components of the Argo program will address this deficit in oxygen measurements. This project will devise an effective sampling protocol for observing ocean oxygen over the full ocean depth. This project will use existing oxygen observations and state-of-the-art numerical tools to provide the first design of a feasible and effective oxygen sampling strategy. The focus is on the role of Deep Argo. This work will calculate the float populations and distributions required to resolve oxygen changes over time and space. At the same time, this work will account for the accuracy and stability of oxygen measuring instruments. Numerical models will be used to determine how historical and additional oxygen data can reduce the uncertainty in understanding of ongoing ocean oxygen loss. Through the course of the project, the researchers will lead several events and create teaching materials to engage the next generation of ocean scientists. They will communicate the importance of ocean oxygen loss, the influence of climate change, and the opportunity to better protect ecosystems through improved oxygen monitoring.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.

海洋是需要氧气来呼吸的大型生命形式和产生我们最终呼吸的氧气的一半左右的小型生命形式的家园。令人担忧的是，观测记录表明，海洋正在失去其氧气含量。最先进的气候模型预测，这一趋势将持续到世纪末。由于数据覆盖范围有限，氧气损失的速率和原因非常不确定。近年来，我们通过Argo计划剖面浮标队的测量，对海洋的盐度和温度变化有了很大的了解。到目前为止，大多数浮标还没有测量氧气。Argo计划的生物地球化学（在2000米以上运行）和深层（4000至6000米）部分的拟议扩展将解决氧气测量方面的这一不足。该项目将设计一个有效的采样协议，用于在整个海洋深度观测海洋氧气。 该项目将使用现有的氧气观测和最先进的数值工具，提供可行和有效的氧气采样策略的第一个设计。重点是深度Argo的作用。这项工作将计算解决氧气随时间和空间的变化所需的浮动人口和分布。同时，这项工作将占氧测量仪器的准确性和稳定性。数值模型将用于确定历史和额外的氧气数据如何减少对持续海洋氧气损失的理解的不确定性。在整个项目过程中，研究人员将领导几项活动，并编写教材，以吸引下一代海洋科学家。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。