Sampling Peculiarity of Sea Surface Temperature Data Sets from Drifting Buoys due to the Lagrangian Nature of Observing Platforms

由于观测平台的拉格朗日性质，从漂流浮标中采样海面温度数据集的特殊性

• 批准号: 1853717
• 负责人: Alexey Kaplan
• 金额: $ 39.21万
• 依托单位: Columbia University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-01 至 2023-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1853717&HistoricalAwards=false
• 关键词: Sampling; Peculiarity; Sea; Surface; Temperature

Drifting buoys are a common platform for observing surface ocean currents and sea surface temperature (SST). Their sampling is Lagrangian, meaning that they move with the ocean currents, as opposed to other observational platforms which are fixed in space (Eulerian) or move in some other manner (like ships). This project will investigate the effects that moving with the currents has on the differences between SST measured from drifters with SST observed from satellite. The hypothesis is that there is a bias completely due to the Lagrangian sampling which can be quantified and corrected for. The project has important implications for improving the SST data sets that are used for initialization or assimilation in climate models. The project will involve undergraduate students in the research. The results will be made publicly available and will be presented at the LDEO Open House and at an Earth2Class workshop for K-12 Earth Science teachers.The project focuses on the sampling interdependency of SST observations from drifting buoys that occurs due to their Lagrangian nature, combined with the approximately conservative property of SST. It is hypothesized that root mean square differences between SST measured from drifting buoys and satellite can be quantified as a sampling bias attributable to the Lagrangian nature of the drifters. The research involves quantifying this bias and correcting for it. The project will use SST from drifters and satellite and will use the Mercator ocean model as well. The results are anticipated to be useful for properly initializing climate models with accurate SST fields.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.

漂流浮标是观测表层洋流和海面温度的常用平台。它们的采样是拉格朗日的，这意味着它们随着洋流移动，而不是其他固定在空间（欧拉）或以其他方式移动（如船舶）的观测平台。本项目将研究随海流移动对从漂流物测量的SST与从卫星观测的SST之间的差异的影响。假设存在完全由于拉格朗日采样而导致的偏差，该偏差可以量化和校正。该项目对改进用于气候模式初始化或同化的SST数据集具有重要意义。该项目将让本科生参与研究。结果将公开提供，并将在LDEO开放日和Earth 2Class研讨会上为K-12地球科学教师展示。该项目的重点是SST观测的采样相互依赖性，这些观测来自漂移浮标，由于其拉格朗日性质，结合SST的近似保守属性。据推测，从漂流浮标和卫星测得的SST之间的均方根差异可以量化为一个采样偏差归因于拉格朗日性质的漂流。该研究包括量化这种偏差并对其进行校正。该项目将使用来自漂流者和卫星的SST，并将使用墨卡托海洋模型。该奖项反映了NSF的法定使命，并被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。