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III-posed retrieval of aerosol extinction coefficient profiles from Raman lidar data by regularization

机译:通过正则化从拉曼激光雷达数据获取III姿态的气溶胶消光系数分布图

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In the analysis of Raman lidar measurements of aerosol extinction, it is necessary to calculate the derivative of the logarithm of the ratio between the atmospheric number density and the range-corrected lidar-received power. The statistical fluctuations of the Raman signal can produce large fluctuations in the derivative and thus in the aerosol extinction profile. To overcome this difficult situation we discuss three methods: Tikhonov regularization, variational, and the sliding best-fit (SBF). Three methods are performed on the profiles taken from the European Aerosol Research Lidar Network lidar database simulated at the Raman shifted wavelengths of 387 and 607 nm associated with the emitted signals at 355 and 532 nm. Our results show that the SBF method does not deliver good results for low fluctuation in the profile. However, Tikhonov regularization and the variational method yield very good aerosol extinction coefficient profiles for our examples. With regard to, e.g., the 532 nm wavelength, the L-2 errors of the aerosol extinction coefficient profile by using the SBF, Tikhonov, and variational methods with respect to synthetic noisy data are 0.0015(0.0024), 0.00049(0.00086), and 0.00048(0.00082), respectively. Moreover, the L2 errors by using the Tikhonov and variational methods with respect to a more realistic noisy profile are 0.0014(0.0016) and 0.0012(0.0016), respectively. In both cases the L-2 error given in parentheses concerns the second example. (c) 2008 Optical Society of America.
机译:在分析拉曼激光雷达消灭气溶胶的过程中,有必要计算大气数密度与距离校正后的激光雷达接收功率之比的对数导数。拉曼信号的统计波动会在导数中产生较大波动,从而在气溶胶消光曲线中产生较大波动。为了克服这种困难的情况,我们讨论了三种方法:Tikhonov正则化,变分和滑动最佳拟合(SBF)。在从欧洲气溶胶研究激光雷达网络激光雷达数据库获取的配置文件上执行了三种方法,这些配置文件在与355和532 nm处发射的信号相关的拉曼位移波长387和607 nm处进行了模拟。我们的结果表明,对于轮廓的低波动,SBF方法不能提供良好的结果。但是,对于我们的示例,Tikhonov正则化和变分方法会产生非常好的气溶胶消光系数曲线。对于例如532 nm波长,使用SBF,Tikhonov和变分方法对合成噪声数据的气溶胶消光系数曲线的L-2误差为0.0015(0.0024),0.00049(0.00086)和分别为0.00048(0.00082)。此外,针对更真实的噪声轮廓,使用Tikhonov和变分方法得出的L2误差分别为0.0014(0.0016)和0.0012(0.0016)。在两种情况下,括号中给出的L-2错误均与第二个示例有关。 (c)2008年美国眼镜学会。

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