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Detection of particle layers in backscatter profiles: application to Antarctic lidar measurements

机译:后向散射剖面中颗粒层的检测:在南极激光雷达测量中的应用

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摘要

A detection method is proposed and studied to infer the presence of hidden signals in a statistical way. It is applied here to the detection of Polar Stratospheric Cloud (PSC) layers in lidar backscatter profiles measured over the Dumont D'Urville station (Antarctica). PSCs appear as layers with enhanced variance in non stationary, heteroscedastic signal profiles, between two unknown altitudes to be estimated. The method is based on a three step algorithm. The first step is the stationarization of the signal, the second performs the maximum likelihoods estimation of the signal (PSC altitude range and variance inside and outside the PSC layer). The last step uses a Fisher-Snédécor test to decide whether the detection of PSC layer is statistically significant. Performances and robustness of the method are tested on simulated data with given statistical properties. Bias and detection limit are estimated. The method is then applied to lidar backscatter profiles measured in 2008. No PSC are detected during seasons when PSCs are not expected to form. As expected, PSC layers are detected during the austral winter and early spring. The effect of time averaging of the profiles is investigated. The best compromise for detection of PSC layers in lidar backscatter profiles acquired at Dumont D'Urville is a time averaging window of 1 h typically.
机译:提出并研究了一种检测方法,以统计方式推断隐藏信号的存在。它在这里用于检测在Dumont D'Urville站(南极洲)上测量的激光雷达后向散射剖面中的极地平流层云(PSC)层。 PSC表现为在两个要估计的未知高度之间的非平稳,异方差信号曲线中具有增强的方差的图层。该方法基于三步算法。第一步是信号的平稳化,第二步执行信号的最大似然估计(PSC高度范围和PSC层内外的方差)。最后一步使用Fisher-Snédécor检验来确定PSC层的检测是否具有统计意义。该方法的性能和鲁棒性在具有给定统计特性的模拟数据上进行了测试。估计偏差和检出限。然后将该方法应用于2008年测得的激光雷达后向散射剖面。在预计不会形成PSC的季节中,未检测到PSC。如预期的那样,在南方冬季和初春期间检测到了PSC层。研究了配置文件的时间平均的影响。在Dumont D'Urville获得的激光雷达后向散射剖面中检测PSC层的最佳折衷方法是平均时间窗通常为1小时。

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