Optimizing the utility of satellite altimetry for diagnosing lateral stirring and mixing in the upper ocean

优化卫星测高在诊断上层海洋横向搅拌和混合方面的效用

• 批准号: 0962054
• 负责人: Kendall Smith
• 金额: $ 64.33万
• 依托单位: New York University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-06-01 至 2015-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0962054&HistoricalAwards=false
• 关键词: Optimizing; utility; satellite; altimetry; diagnosing

The project will assess the significance of model error for mixing diagnostics deduced from satellite altimetry products, develop strategies for ameliorating its impact, and expand understanding of the theoretical relationships between measures of mixing. The sensitivity of mixing diagnostics to noise and spatial and temporal sampling resolution will be determined using high resolution primitive equation ocean models. A Lagrangian stochastic parameterization scheme for the unresolved flow will be developed and coupled to the observed flow calculated from satellite altimetry. Mixing diagnostic parameters will be averaged over ensembles of particles to provide statistically meaningful averages and confidence intervals. Data assimilation methods will be exploited to dynamically estimate stochastic parameters based upon successive observations of the flow field. Finally, the research will develop interrelationships among mixing diagnostics and between diagnostics and large-scale features of the flow using analytical techniques, simple kinematic flows, and idealized geophysical turbulence models.The project aims to optimize the utility of satellite altimetry products and develop an extensively documented algorithm that can be utilized with any given gridded altimetry-derived velocity time-series. The results of this research will improve understanding of mixing in the ocean and our ability to model the transport of ocean-borne material with applications to a wide range of marine-based human activities.

该项目将评估模型误差对从卫星测高产品推断的混合诊断的重要性，制定改善其影响的战略，并扩大对混合措施之间理论关系的理解。将使用高分辨率原始方程海洋模型来确定混合诊断对噪声以及空间和时间采样分辨率的敏感性。一个拉格朗日随机参数化方案的未解决的流量将开发和耦合到从卫星测高计算的观测流量。混合诊断参数将在粒子集合上取平均值，以提供具有统计学意义的平均值和置信区间。将利用数据同化方法，根据连续观测流场动态估计随机参数。最后，该研究将利用分析技术、简单的运动学流动和理想化的地球物理湍流模型，发展混合诊断之间以及诊断与流动的大规模特征之间的相互关系，该项目旨在优化卫星测高产品的效用，并开发一种可用于任何给定的网格测高导出速度时间序列的有广泛文件证明的算法。这项研究的结果将提高对海洋混合的理解，并提高我们模拟海洋传播物质运输的能力，并将其应用于广泛的海洋人类活动。