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.

该项目的目标是根据Argo观测结果与数值模式结果之间的比较，定量评估Argo浮标阵列在调查流域至全球尺度上层海洋对飓风的反应方面的能力和局限性。Argo阵列测量风暴前后的次表层温度和盐度剖面，因此提供了一个独特的数据集，用于研究风暴在流域到全球尺度以及次表层和海面的影响。为了正确理解热带风暴在流域到全球尺度的影响，需要建立一个分辨率足以观测热带风暴对表层和次表层海洋影响的持续全球观测网络。另一方面，我们对上层海洋对风暴的反应的理解主要是基于对单个风暴的研究。Argo阵列的全球观测网络与卫星观测相结合的成功使用将使研究人员能够将我们的理解外推到盆地到全球尺度的后果。然而，尽管Argo阵列的近全球和地下覆盖提供了独特的机会，在空间中以相对稀疏的10天间隔进行的不受控制的采样产生了相当大的不确定性，这主要是由于不能过滤掉近距离的，惯性抽水和随机位置的不确定性，相对于风暴和背景流。因此，需要一种方法来量化海洋对飓风反应的Argo采样的不确定性，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和飓风强迫下，使用真实的数值海洋模拟来进行观测取样实验。在实验过程中，将在模型中部署虚拟浮标，以模拟真实的海洋中的Argo浮标。通过虚拟浮子剖面采样的数据将用于估计模拟全响应的不确定性。3维Price-Weller-Pinkel模型将被用于进行观测抽样实验。智力优点：以统计学上稳健的方式评估不受控制的Argo观测对飓风反应的不确定性是前所未有的（据我们所知）。拟议的活动不仅将提高该社区将统计方法应用于分散观测的能力，而且还将使其能够利用阿尔戈观测来解决与流域规模海洋对飓风的反应有关的基本科学问题，例如热带风暴对海洋上层的垂直混合和热的纬向输送的贡献。更广泛的影响我们的工作将这将为更广泛的海洋学和大气科学界提供一个强有力的统计工具，利用Argo观测研究上层海洋对飓风等极端事件的反应及相关的海气相互作用，Argo阵列的这一应用远远超出了其最初的设想。Argo是国际社会的一项长期努力，从大规模海洋学到年际至十年期可预测性的努力，使许多领域受益。扩大Argo阵列的使用将是非常可取的，有利于证明这一社区资产的扩展和扩展。该项目还将有助于两名有前途的新NSF研究人员的职业发展。