首页> 外文学位 >Using clear-air adjoint-method wind retrievals from the WSR-88D network to initialize a mesocale model in a pre-convective environment.
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Using clear-air adjoint-method wind retrievals from the WSR-88D network to initialize a mesocale model in a pre-convective environment.

机译:使用来自WSR-88D网络的晴空伴生风回风法在对流环境中初始化中尺度模型。

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摘要

A clear-air adjoint-method (CAAM) wind retrieval scheme is developed to accurately depict wind flow over a mesoscale domain using WSR-88D data. The CAAM is based upon the simple adjoint method that incorporates predictive equations for reflectivity and radial wind, treating them as passive scalars. These equations are used to retrieve the horizontally varying time-mean wind that gives the best estimate of the observed fields during the retrieval period. The optimal simulation of the observed field is obtained through minimizing, in a least squares sense, a cost function representing discrepancies between the estimated and observed quantities such as reflectivity and radial wind.; The CAAM is applied to both idealized atmospheric regimes and real-data cases containing various configurations of atmospheric structures. Accurate retrieval solutions are shown to depend on the initial conditions of the technique and the existence of coherent gradients within the radar observation fields.; Data void regions exist between WSR-88D radars even though they are sensitive enough to detect clear-air returns up to and sometimes greater than 100 km away. Thus, when initializing a mesoscale numerical weather prediction model, observation information from multiple CAAM wind retrievals over a mesoscale region must be spread across the entire model domain. This is accomplished using a Cressman successive correction method of objective analysis with an “air mass” weighting scheme. The weighting scheme does not allow retrieved wind information to be spread across a detected boundary but only within the same air mass in which it resides.; Application of the assimilation technique is demonstrated in a numerical simulation of a mesoscale convective system initiated along a stationary boundary in weak, synoptic flow using retrieved wind information from seven WSR-88D radars. The assimilated retrieved winds significantly affect the horizontal convergence along the stationary boundary producing a more realistic spatial distribution of precipitation in the first couple of hours of the simulation. Furthermore, the orientation of the resultant cold pool and outflow boundary generated by the convective system is modified. Hence, the location and amount of lift along the outflow boundary is altered resulting in a more accurate simulated evolution of subsequent convection.
机译:开发了一种清晰的空气伴随方法(CAAM)风检索方案,以使用WSR-88D数据准确地描绘中尺度域上的风流。 CAAM基于简单的伴随方法,该方法结合了反射率和径向风的预测方程,将它们视为无源标量。这些方程式用于检索水平变化的时均风,它在检索期间给出了对观测场的最佳估计。通过在最小二乘意义上最小化表示估计量和观测量之间的差异(例如反射率和径向风)的成本函数,可以获得观测场的最佳模拟。 CAAM适用于理想的大气状况和包含各种大气结构配置的实际数据案例。结果表明,准确的检索解决方案取决于该技术的初始条件以及雷达观测场内相干梯度的存在。 WSR-88D雷达之间存在数据无效区域,即使它们足够灵敏,也可以检测到甚至有时超过100公里以外的晴空返回。因此,当初始化中尺度数值天气预报模型时,来自中尺度区域多个CAAM风场的观测信息必须分布在整个模型域中。这是通过使用“空气质量”加权方案的客观分析的Cressman连续校正方法来完成的。加权方案不允许将检索到的风信息散布在检测到的边界上,而只能散布在它所驻留的相同空气质量内。利用从七个WSR-88D雷达检索到的风信息,在弱天气流中沿着静止边界发起的中尺度对流系统的数值模拟中证明了同化技术的应用。在模拟的前几个小时中,吸收的同化风会显着影响沿静止边界的水平收敛,从而产生更现实的降水空间分布。此外,对流系统产生的最终冷池和流出边界的方向也进行了修改。因此,沿着流出边界的升力的位置和量被改变,从而导致随后对流的更精确的模拟演变。

著录项

  • 作者

    Porter, Christopher Woods.;

  • 作者单位

    The Pennsylvania State University.;

  • 授予单位 The Pennsylvania State University.;
  • 学科 Physics Atmospheric Science.; Geophysics.
  • 学位 Ph.D.
  • 年度 2003
  • 页码 175 p.
  • 总页数 175
  • 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;
  • 关键词

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