SGER: Quantification of Uncertainty in Argo Observation of Ocean Response to Hurricanes

SGER：Argo 飓风海洋响应观测不确定性的量化

• 批准号: 0847160
• 负责人: Young-Oh Kwon
• 金额: $ 9.02万
• 依托单位: Woods Hole Oceanographic Institution
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-11-01 至 2011-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0847160&HistoricalAwards=false
• 关键词: SGER; Quantification; Uncertainty; Argo; Observation

The objective of this project is to assess quantitatively the capability and limitations of the Argo float array for the investigation of basin-to-global scale upper ocean response to hurricanes based on the comparison between the Argo observation and numerical model results. The Argo array measures subsurface temperature and salinity profiles before and after storms, and so provides a unique dataset to study the impact of the storms in a basin-to-global scale and for the subsurface as well as the sea surface.To properly understand the basin-to-global scale impact of tropical storms, a sustained global observational network with a resolution sufficient to observe the impact of tropical storms is needed for surface as well as the subsurface ocean. On the other hand, our understanding on the upper ocean response to the storms has progressed mostly based on the studies focused on individual storms.Successful use of the global observational network of Argo array in conjunction with satellite observations would allow the investigators to extrapolate our understanding to basin-to-global scale consequences.However, despite the unique opportunity provided by the near-global and subsurface coverage of the Argo array, the uncontrolled sampling in space with a relatively sparse 10 day interval produces substantial uncertainty primarily due to the inability to filter out near-inertial pumping and randomposition uncertainties with respect to the storm and the background flow. Therefore, a method to quantify uncertainty in the Argo sampling of ocean response to the hurricane is needed as a prerequisite to addressthe scientific questions using the dataset. The main strategy is to use a realistic numerical ocean simulation under a given initial background condition and hurricane forcing to perform an observation sampling experiment. During the experiments, virtual floats will be deployed in the model to mimic Argo floats in the real ocean. The data sampled by virtual float profiles will be used to estimate the uncertainty against the simulated full response. The 3-dimensional Price-Weller-Pinkel model will be used to perform observation sampling experiment.Intellectual Merit:Assessing uncertainty of the uncontrolled Argo observation in a statistically robust fashion with respect to the response to hurricane is unprecedented (as far as we are aware of). The proposed activity will not only advance the community's capability to apply statistical methods to scattered observations, but also enable it to use the Argo observations to address the fundamental scientific questions associated with the basin-scale ocean response to the hurricane, such as what is the contribution of tropical storms to the vertical mixing and the meridional transport of heat in the upper ocean.Broader ImpactsOur proposed work will provide the broader oceanography and atmospheric science community with a statistically robust tool to use the Argo observations to study the upper ocean response to an extreme event such as the hurricane and associated air-sea interaction, an application of Argo array that is well beyond its original vision. Argo has been a long-term international community effort that benefited many areas from the large-scale oceanography to the interannual-to-decadal predictability efforts. Broadeningthe use of Argo array will be very desirable and beneficial to justify the extension and expansion of this community asset. The project will also contirubte to the careeer development of two promising new NSF investigators.

该项目的目的是根据ARGO观察结果与数值模型结果之间的比较来定量评估Argo Float阵列的能力和局限性，以研究盆地到全球尺度上海对飓风的反应。 Argo阵列测量暴风雨前后的地下温度和盐度剖面，因此提供了一个独特的数据集来研究风暴在盆地到全球尺度以及地下以及海面的影响。热带风暴的盆地到全球量表的影响是一个持续的全球观察网络，其分辨率足以观察到地面和地下海洋的热带风暴的影响。另一方面，我们对上海对风暴的反应的理解主要是基于关注单个风暴的研究。成功地利用了Argo Array的全球观察网络以及卫星观察结果，使研究人员能够超越我们的理解。盆地到全球量表的后果。但是，尽管近乎全球和地下的覆盖范围是Argo Array的独特机会，但在太空中的不受控制的采样，相对较少的10天间隔却产生了实质性的不确定性，主要是由于无能为力。过滤掉几乎惯性的抽水和兰型组件不确定性相对于风暴和背景流。因此，需要一种量化海洋对飓风反应反应的不确定性的方法，作为使用数据集解决科学问题的先决条件。主要策略是在给定的初始背景条件下使用现实的数值海洋模拟，并强迫执行观察采样实验。在实验过程中，虚拟浮子将部署在模型中，以模仿Argo浮子在真实的海洋中。虚拟浮点轮廓采样的数据将用于估计模拟完整响应的不确定性。三维价格挡板 - 粉红色模型将用于执行观察抽样实验。智务优点：评估未受控制的ARGO观察的不确定性，以统计上强大的方式在对飓风的反应方面是没有预期的的）。拟议的活动不仅将提高社区将统计方法应用于分散观察的能力，而且还可以使其能够使用Argo观察来解决与盆地规模海洋对飓风的反应相关的基本科学问题，例如什么是什么热带风暴对垂直混合的贡献和上海中的热量的子午运输。BroaderImplastsour拟议的工作将为更广泛的海洋学和大气科学界提供一种统计坚固的工具，可以利用ARGO观测来研究上海上海洋的反应极端事件，例如飓风和相关的空中互动，这是Argo阵列的应用，远远超出了其原始视野。 Argo一直是一项长期的国际社会努力，从大规模海洋学到年间到十年的可预测性努力都使许多领域受益。扩大对Argo阵列的使用将是非常理想的和有益的，可以证明该社区资产的扩展和扩展是合理的。该项目还将引发两个有前途的新NSF调查人员的护理人发展。