Abstract

The retrieval of the extinction coefficients of aerosols and clouds without assumptions is the most important advantage of the high-spectral-resolution lidar (HSRL). The standard method to retrieve the extinction coefficient from HSRL signals depends heavily on the signal-to-noise ratio (SNR). In this work, an iterative image reconstruction (IIR) method is proposed for the retrieval of the aerosol extinction coefficient based on HSRL data, this proposed method manages to minimize the difference between the reconstructed and raw signals based on reasonable estimates of the lidar ratio. To avoid the ill-posed solution, a regularization method is adopted to reconstruct the lidar signals in the IIR method. The results from Monte-Carlo (MC) simulations applying both standard and IIR methods are compared and these comparisons demonstrate that the extinction coefficient and the lidar ratio retrieved by the IIR method have smaller root mean square error (RMSE) and relative bias values than the standard method. A case study of measurements made by Zhejiang University (ZJU) HSRL is presented, and their results show that the IIR method not only obtains a finer structure of the aerosol layer under the condition of low SNR, but it is also able to retrieve more reasonable values of the lidar ratio.

Highlights

  • Accurate measurements of atmospheric aerosol properties are essential to the study of climate change, since aerosols affect the Earth’s climate system by scattering and absorbing solar radiation, as well as influencing the cloud properties [1]

  • The mean relative bias of the lidar ratio obtained by the iterative image reconstruction (IIR) method is 8.5%, while it is up to 22.6% with the standard method

  • The comparison based on the MC simulations between the standard method and the IIR method demonstrates that our proposed method yields the aerosol extinction coefficient and the lidar ratio with smaller root mean square error (RMSE) and relative bias

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Summary

Introduction

Accurate measurements of atmospheric aerosol properties are essential to the study of climate change, since aerosols affect the Earth’s climate system by scattering and absorbing solar radiation, as well as influencing the cloud properties [1]. The requirement for a priori assumptions of the lidar ratio in the retrieval of aerosol optical properties limits the accuracy of elastic backscatter lidars [3,4,5]. Raman Lidar permits the independent measurement of aerosol extinction coefficient and backscatter coefficient by detecting the elastic and Raman scattering signals, but it is mainly used during nighttime because of the large background radiation in daytime [6]. The aerosol backscatter coefficient and extinction coefficient can be retrieved directly in HSRL [6,7,8]

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