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A generalised background correction algorithm for a Halo Doppler lidar and its application to data from Finland

机译:Halo多普勒激光雷达的广义背景校正算法及其在芬兰数据中的应用

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Current commercially available Doppler lidars provide an economical and robust solution for measuring vertical and horizontal wind velocities, together with the ability to provide co- and cross-polarised backscatter profiles. The high temporal resolution of these instruments allows turbulent properties to be obtained from studying the variation in radial velocities. However, the instrument specifications mean that certain characteristics, especially the background noise behaviour, become a limiting factor for the instrument sensitivity in regions where the aerosol load is low. Turbulent calculations require an accurate estimate of the contribution from velocity uncertainty estimates, which are directly related to the signal-to-noise ratio. Any bias in the signal-to-noise ratio will propagate through as a bias in turbulent properties. In this paper we present a method to correct for artefacts in the background noise behaviour of commercially available Doppler lidars and reduce the signal-to-noise ratio threshold used to discriminate between noise, and cloud or aerosol signals. We show that, for Doppler lidars operating continuously at a number of locations in Finland, the data availability can be increased by as much as 50% after performing this background correction and subsequent reduction in the threshold. The reduction in bias also greatly improves subsequent calculations of turbulent properties in weak signal regimes.
机译:当前的市售多普勒激光雷达为测量垂直和水平风速提供了一种经济,可靠的解决方案,并具有提供共极化和交叉极化的反向散射轮廓的能力。这些仪器的高时间分辨率允许通过研究径向速度的变化获得湍流特性。但是,仪器的规格意味着某些特性,尤其是背景噪声的行为,已成为气溶胶负荷低的地区仪器灵敏度的限制因素。湍流计算需要对速度不确定性估计的贡献进行准确的估计,而速度不确定性估计与信噪比直接相关。信噪比的任何偏差都将作为湍流特性的偏差传播。在本文中,我们提出了一种方法来校正市售多普勒激光雷达的背景噪声行为中的伪影,并降低用于区分噪声与云或气溶胶信号的信噪比阈值。我们表明,对于在芬兰多个地点连续运行的多普勒激光雷达,在执行此背景校正并随后降低阈值后,数据可用性可以提高多达50%。偏置的减小还大大改善了弱信号状态下湍流特性的后续计算。

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