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Raman lidar measurements for boundary layer gradients and atmospheric refraction of millimeter-wave signals

机译:拉曼激光雷达测量边界层梯度和毫米波信号的大气折射

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The atmospheric boundary layer is typically characterized by a higher water vapor content and higher temperature than the free troposphere above it. Its height increases as the size of convection cells grow during the morning due to surface heating, stabilizes during the day, and it collapses as the energy input decreases in the evening. The marine boundary layer emphasizes these aspects. The large temperature gradients, humidity gradients and shear at the top of the boundary layer impact several processes, such as changes in both propagation properties as a function of wavelength and aerosol size distributions. We use Raman lidar to measure the gradients, and investigate several data inversion techniques to determine the best approach to obtain a high accuracy, for high SNR profiles of these gradients. Methods include anisotropic averaging between height and range, and averaging only to the level required for a specific target SNR. Examples that benefit from different time and range averaging will be given. The methods for gradient calculations and the interaction with pre- or post-averaging are also investigated. We model the impact of gradient-profile measurement from errors in the refraction of radar beams as a measure of quality requirements.
机译:大气边界层通常具有比其上方的自由对流层更高的水蒸气含量和更高的温度的特征。由于对流单元的大小在早上由于表面加热而增加,其高度增加,在白天稳定,并且随着晚上能量输入的减少而塌陷。海洋边界层强调了这些方面。边界层顶部的大温度梯度,湿度梯度和剪切力影响几个过程,例如传播特性随波长和气溶胶尺寸分布的变化。我们使用拉曼激光雷达测量梯度,并研究了几种数据反演技术,以确定针对这些梯度的高SNR分布图获得高精度的最佳方法。方法包括高度和范围之间的各向异性平均,以及仅平均到特定目标SNR所需的水平。将给出受益于不同时间和范围平均的示例。还研究了梯度计算的方法以及与前平均或后平均的交互作用。我们对雷达轮廓线折射误差中的梯度剖面测量的影响进行建模,以作为质量要求的量度。

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