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A novel post-processing algorithm for Halo Doppler lidars

机译:卤素多普勒雷达尔的新型后处理算法

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Commercially available Doppler lidars have now been proven to be efficient tools for studying winds and turbulence in the planetary boundary layer. However, in many cases low signal-to-noise ratio is still a limiting factor for utilising measurements by these devices. Here, we present a novel post-processing algorithm for Halo Stream Line Doppler lidars, which enables an improvement in sensitivity of a factor of 5 or more. This algorithm is based on improving the accuracy of the instrumental noise floor and it enables longer integration times or averaging of high temporal resolution data to be used to obtain signals down to -32 dB. While this algorithm does not affect the measured radial velocity, it improves the accuracy of radial velocity uncertainty estimates and consequently the accuracy of retrieved turbulent properties. Field measurements using three different Halo Doppler lidars deployed in Finland, Greece and South Africa demonstrate how the new post-processing algorithm increases data availability for turbulent retrievals in the planetary boundary layer, improves detection of high-altitude cirrus clouds and enables the observation of elevated aerosol layers.
机译:商业上可获得的多普勒·莱德斯目前已被证明是在行星边界层中研究风和湍流的有效工具。然而,在许多情况下,低信噪比仍然是利用这些设备的测量的限制因素。在这里,我们提出了一种新的卤素流线多普勒LIDAR后处理算法,其能够改善5倍或更多的灵敏度。该算法基于提高仪器噪声底板的准确性,并且它使得能够更长的集成时间或对高时分辨率数据的平均来用于将信号降至-32 dB。虽然该算法不影响测量的径向速度,但它提高了径向速度不确定性估计的准确性,从而提高了检索到的湍流性能的准确性。使用三种不同的光环多普勒利尔德在芬兰,希腊和南非部署的现场测量演示了新的后处理算法如何增加行星边界层中湍流检索的数据可用性,从而提高了高海拔云云的检测,并实现了升高的观察气溶胶层。

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