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WRF nested large-eddy simulations of deep convection during SEAC4RS

机译:WRF嵌套SEAC4RS期间深对流的大涡模拟

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摘要

Deep convection is an important component of atmospheric circulations that affects many aspects of weather and climate. Therefore, improved understanding and realistic simulations of deep convection are critical to both operational and climate forecasts. Large-eddy simulations (LESs) often are used with observations to enhance understanding of convective processes. This study develops and evaluates a nested-LES method using the Weather Research and Forecasting (WRF) model. Our goal is to evaluate the extent to which the WRF nested-LES approach is useful for studying deep convection during a real-world case. The method was applied on 2 September 2013, a day of continental convection having a robust set of ground and airborne data available for evaluation. A three domain mesoscale WRF simulation is run first. Then, the finest mesoscale output (1.35 km grid length) is used to separately drive nested-LES domains with grid lengths of 450 and 150 m. Results reveal that the nested-LES approach reasonably simulates a broad spectrum of observations, from reflectivity distributions to vertical velocity profiles, during the study period. However, reducing the grid spacing does not necessarily improve results for our case, with the 450 m simulation outperforming the 150 m version. We find that simulated updrafts in the 150 m simulation are too narrow to overcome the negative effects of entrainment, thereby generating convection that is weaker than observed. Increasing the sub-grid mixing length in the 150 m simulation leads to deeper, more realistic convection, but comes at the expense of delaying the onset of the convection. Overall, results show that both the 450 m and 150 m simulations are influenced considerably by the choice of sub-grid mixing length used in the LES turbulence closure. Finally, the simulations and observations are used to study the processes forcing strong midlevel cloud-edge downdrafts that were observed on 2 September. Results suggest that these downdrafts are forced by evaporative cooling due to mixing near cloud edge and by vertical perturbation pressure gradient forces acting to restore mass continuity around neighboring updrafts. We conclude that the WRF nested-LES approach provides an effective method for studying deep convection for our real-world case. The method can be used to provide insight into physical processes that are important to understanding observations. The WRF nested-LES approach could be adapted for other case studies in which high-resolution observations are available for validation.
机译:深对流是影响天气和气候许多方面的大气环流的重要组成部分。因此,对深对流的了解和逼真的模拟对于运行和气候预报都至关重要。大涡模拟(LESs)通常与观测结果结合使用,以增强对流过程的理解。这项研究使用天气研究和预报(WRF)模型开发和评估嵌套LES方法。我们的目标是评估WRF嵌套LES方法在实际案例中对研究深对流有用的程度。该方法于2013年9月2日(大陆对流的一天)应用,该数据具有可用于评估的一组可靠的地面和空中数据。首先运行三域中尺度WRF仿真。然后,最好的中尺度输出(1.35 km网格长度)用于分别驱动网格长度为450和150 m的嵌套LES域。结果表明,在研究期间,嵌套LES方法合理地模拟了从反射率分布到垂直速度剖面的广泛观测。但是,减小网格间距并不一定会改善我们的情况,因为450 m模拟的效果优于150 m版本。我们发现150 m模拟中的模拟上升气流太窄,无法克服夹带的负面影响,从而产生比观测到的对流弱的对流。在150 m模拟中增加子网格的混合长度会导致更深,更逼真的对流,但以延迟对流的开始为代价。总体而言,结果表明,在LES湍流封闭中使用的子网格混合长度的选择对450 m和150 m的模拟都有很大影响。最后,模拟和观察结果被用来研究强迫9月2日观测到的强中层云边缘下降气流的过程。结果表明,这些下降气流是由于云边缘附近的混合所致的蒸发冷却和垂直扰动压力梯度力的作用,以恢复相邻上升气流周围的质量连续性。我们得出的结论是,WRF嵌套LES方法为研究我们的实际案例提供了一种有效的方法来研究深度对流。该方法可用于深入了解对于理解观测非常重要的物理过程。 WRF嵌套LES方法可以适用于其他案例研究,在这些案例研究中可以使用高分辨率观测值进行验证。

著录项

  • 作者

    Heath, Nicholas Kyle.;

  • 作者单位

    The Florida State University.;

  • 授予单位 The Florida State University.;
  • 学科 Meteorology.;Atmospheric sciences.
  • 学位 Ph.D.
  • 年度 2015
  • 页码 109 p.
  • 总页数 109
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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