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Assimilation of future ocean-current measurements from satellites

卫星对未来洋流测量的同化

基本信息

批准号：
2600410
负责人：
金额：
--
依托单位：
University of Reading
依托单位国家：
英国
项目类别：
Studentship
财政年份：
2021
资助国家：
英国
起止时间：
2021 至无数据
项目状态：
未结题

来源：
https://gtr.ukri.org/projects?ref=studentship-2600410
关键词：
Assimilation future ocean current measurements

项目摘要

Over the coming years space agencies plan to launch satellite instruments that can measure the ocean surface current velocity. Ingesting such measurements into ocean models using data assimilation has the potential to increase accuracy of forecasts of the ocean itself, and of the atmosphere through coupled modelling. In order to achieve this, it is necessary to build an assimilation system that treats the rotational and divergent parts of the velocity separately, since then the errors in these two components can be assumed to be approximately uncorrelated. This is commonly done in atmospheric forecasting systems, where the wind is decomposed into the streamfunction and velocity potential within the assimilation scheme. However, the presence of coastlines in ocean models makes this much harder to do for the ocean. The decomposition of the currents into their rotational and divergent parts requires the solution of an elliptic equation, a problem that is ill-posed in the presence of coastal boundary conditions. Methods to overcome this problem have been proposed in the literature with different assumptions, but none have been implemented within ocean data assimilation systems. In this project we will investigate the following questions: - How can ocean velocity fields be decomposed into their rotational and divergent parts in a way that is numerically stable?- Does this decomposition lead to fields whose errors are uncorrelated? Are there better decompositions to use, e.g. based on potential vorticity? - How can such decompositions be used to assimilate future ocean current measurements?

在未来几年，航天局计划发射卫星仪器，可以测量海洋表面的流速。利用数据同化将这些测量结果纳入海洋模型，有可能提高海洋本身预报的准确性，并通过耦合建模提高大气预报的准确性。为了实现这一点，有必要建立一个同化系统，分别处理速度的旋转和发散部分，因为这两个分量的误差可以假设为近似不相关。这通常在大气预报系统中进行，其中风被分解为同化方案中的流函数和速度势。然而，海洋模型中海岸线的存在使得海洋更难做到这一点。分解成旋转和发散部分的电流需要一个椭圆方程的解决方案，这是一个问题，不适定的海岸边界条件的存在。文献中提出了克服这一问题的方法，但采用了不同的假设，但尚未在海洋数据同化系统中实施。在这个项目中，我们将研究以下问题：-如何将海洋速度场分解为它们的旋转和发散部分，以一种数值稳定的方式？-这种分解是否会导致错误不相关的字段？是否有更好的分解方法可供使用，例如基于位涡的方法？- 如何利用这种分解来同化未来的洋流测量？