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Assimilation of global positioning system radio occultation measurements into numerical weather forecast systems.

机译：将全球定位系统的无线电掩星测量同化为数值天气预报系统。

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摘要

2004 marks the centennial of Bjerknes' conceptual solution to the problem of weather forecasting, based on the application of physical and mechanical laws to a set of initial conditions. Today many satellites observe our atmosphere to help provide these initial conditions to numerical weather forecast systems. However, there is still considerable room for improvement when it comes to weather forecasts, namely by better constraining the atmospheric initial conditions through more frequent and more accurate atmospheric observations. The radio occultation (RO) technique which observes the atmosphere from the side (instead of from above, like today's numerous weather satellites) was used for decades to study planetary atmospheres before it was finally used observe our atmosphere. The level of accuracy required in order to make RO competitive with or superior to other techniques already observing the atmosphere was achieved with the advent of the Global Positioning System (CPS) and later with advanced CPS receiver technology. We demonstrate here that useful one-dimensional (1D) vertical atmospheric temperature information can be retrieved from GPS RO refractive index measurements. We develop a first-generation system capable of retrieving that information from real CPS RO refractive index measurements, and assimilating it into a numerical weather forecast system. Resulting five day weather forecasts issued with that system show improved accuracy in the Northern hemisphere and degraded accuracy in the Southern hemisphere. Analyzing data from late CPS RO missions onboard CHAMP and SAC-C satellites, we find that improved receiver technology and processing techniques yield more CPS RO data and of better quality. We develop a two-dimensional (2D) ray-tracing iterative procedure to simulate CPS RO measurements from the three-dimensional (3D) atmospheric representation provided by a numerical weather forecast system. We demonstrate that the 2D ray-tracing results agree better with the CHAMP and SAC-C measurements than the 1D approach used in our first-generation system. In order to render the use of this type of modelling possible under the stringent time constraints of operational numerical weather prediction centers, we propose a new operator called the Fast Atmospheric Refractivity Gradient Operator (FARGO). FARGO is shown to be 250 times faster and nearly as efficient as 2D ray-tracing in fitting real observations. The work presented here will serve to implement a second-generation assimilation system of CPS RO data into numerical weather forecast systems. Also, the approach used in FARGO can be extended to simulate other refraction measurements which suffer from horizontal inhomogeneities in the Earth's lower troposphere.
机译：2004年是Bjerknes在将物理和机械定律应用于一系列初始条件的基础上，对天气预报问题的概念解决方案百年纪念。今天，许多卫星观测我们的大气层，以帮助为数值天气预报系统提供这些初始条件。但是，在天气预报方面仍存在很大的改进空间，即通过更频繁，更准确的大气观测来更好地约束大气初始条件。无线电掩星（RO）技术从侧面（而不是像今天许多气象卫星那样从上方）观察大气，数十年来一直用于研究行星大气，然后才最终用于观测我们的大气。随着全球定位系统（CPS）的出现，以及后来采用先进的CPS接收器技术的出现，使RO具备竞争优势或优于已经观测到的其他技术所需的精度水平。我们在这里证明可以从GPS RO折射率测量中检索出有用的一维（1D）垂直大气温度信息。我们开发了第一代系统，该系统能够从实际CPS RO折射率测量中检索该信息，并将其吸收到数值天气预报系统中。该系统发布的结果为五天天气预报显示，北半球的精度有所提高，而南半球的精度却有所下降。分析来自CHAMP和SAC-C卫星的CPS RO后期任务的数据，我们发现改进的接收器技术和处理技术可以产生更多的CPS RO数据，并且质量更高。我们开发了一个二维（2D）射线跟踪迭代过程，以从数值天气预报系统提供的三维（3D）大气表示中模拟CPS RO测量。我们证明，与第一代系统中使用的一维方法相比，二维射线追踪结果与CHAMP和SAC-C测量结果更好地吻合。为了在操作数值天气预报中心的严格时间限制下使使用这种类型的模型成为可能，我们提出了一种称为快速大气折射率梯度算子（FARGO）的新算子。事实证明，FARGO的速度是250倍，并且其效率与2D射线追踪几乎一样，可以拟合真实的观测结果。这里介绍的工作将用于将CPS RO数据的第二代同化系统实现为数值天气预报系统。此外，FARGO中使用的方法可以扩展为模拟其他折射测量，这些测量在地球对流层较低处受到水平不均匀性的影响。

著录项

  • 作者

    Poli, Paul.;

  • 作者单位

    University of Maryland, Baltimore County.;

  • 授予单位 University of Maryland, Baltimore County.;
  • 学科 Physics Atmospheric Science.; Geophysics.; Physics Optics.
  • 学位 Ph.D.
  • 年度 2004
  • 页码 122 p.
  • 总页数 122
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 大气科学（气象学）;地球物理学;光学;
  • 关键词

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