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Inversion of aerosol size distribution by using genetic algorithms and multi-sensor data

机译:利用遗传算法和多传感器数据反演气溶胶粒径分布

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摘要

In this article, we introduce the genetic algorithm into the inversion of aerosol size distribution. We are often faced with limited or insufficient observations in remote sensing and the observations are contaminated. The particle spectrum extinction equation is an ill-posed integral equation of the extinction inversion method. To overcome the ill-posed nature, we use a double logarithmic normal distribution function to express the aerosol size distribution. To obtain the optimal solution, we introduce the genetic algorithm to gain the minimum sum of squared errors. Our method can improve accuracy and reduce the computational difficulty. The assumption of parameters in the bimodal distribution function is important to the inversion results. The aerosol size distribution obtained from the GRIMM 180 PM monitor and the TSI Scanning mobility particle sizers is compared with that computed via the method proposed by Dubovik and King(2000). Obvious difference has been discovered between aerosol size distribution on the ground and in the total atmospheric column. As a result, it is necessary to develop multi-wavelength and multi-function lidar to get observe the three-dimensional distribution characteristics of aerosol.
机译:在本文中,我们将遗传算法引入到气溶胶粒径分布的反演中。我们经常在遥感中面临有限或不足的观察,而且这些观察被污染了。粒子光谱消光方程是消光反演方法的不适定积分方程。为了克服不适的特性,我们使用双对数正态分布函数来表示气溶胶尺寸分布。为了获得最佳解,我们引入了遗传算法来获得平方误差的最小和。我们的方法可以提高准确性并降低计算难度。双峰分布函数中参数的假设对于反演结果很重要。将通过GRIMM 180 PM监测仪和TSI扫描迁移率粒度仪获得的气溶胶粒径分布与通过Dubovik and King(2000)提出的方法计算得到的气溶胶粒径分布进行比较。已发现地面上的气溶胶尺寸分布与总大气柱中的气溶胶尺寸分布之间存在明显差异。因此,有必要开发多波长和多功能激光雷达来观察气溶胶的三维分布特征。

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