Collaborative Research: Using models and historical data to guide effective monitoring and enhance understanding of deep ocean oxygen variability
Collaborative Research: Using models and historical data to guide effective monitoring and enhance understanding of deep ocean oxygen variability
批准号:
2242743
负责人:
Helen Pillar
金额:
$12.57万
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
项目状态:
未结题
起止时间:
2023-05-01 至 2026-04-30
中文摘要
海洋是大型生命形式的家园,它们需要氧气来呼吸,而小型生命形式产生的氧气约占我们最终呼吸的一半。令人担忧的是,观测记录表明海洋正在失去其氧含量。最先进的气候模式预测,这一趋势将持续到21世纪末。由于数据覆盖稀疏,氧损失的速率和原因高度不确定。近年来,我们对海洋的盐度和温度变化有了很大的了解,这是由“阿尔戈”计划的剖面浮标船队所做的测量结果。到目前为止,大多数浮标都没有测量过氧气。Argo计划的生物地球化学(在2000米以上运行)和深海(4000至6000米)部分的拟议扩展将解决氧气测量的这一缺陷。该项目将设计一个有效的采样方案,以观测整个海洋深度的海洋氧气。该项目将使用现有的氧气观测和最先进的数值工具来提供一个可行和有效的氧气采样策略的第一个设计。重点是深阿尔戈的作用。这项工作将计算浮子的数量和分布,以解决氧气随时间和空间的变化。同时,对氧测量仪器的精度和稳定性也有一定的说明。数值模式将用于确定历史和额外的氧气数据如何减少对正在发生的海洋氧气损失的不确定性。在整个项目过程中,研究人员将领导几次活动,并制作教材,以吸引下一代海洋科学家。他们将宣传海洋氧气损失的重要性、气候变化的影响,以及通过改进氧气监测来更好地保护生态系统的机会。该奖项反映了美国国家科学基金会的法定使命,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。
英文摘要
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.
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