Development of ZJU High-Spectral-Resolution Lidar for Aerosol and Cloud: Extinction Retrieval

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.

Added Value of Aerosol Observations of the Future AOS High Spectral Resolution Lidar with Respect to a Classic Backscatter Spaceborne Lidar Measurements

“…Still in the case of AOS_HSRL, the retrieval of aerosol backscatter profiles show larger errors over the notrhern part of the smoke plume (exceeding 40%), and globally everywhere oscillating between -30% and 30% when the backscatter falls below 10 −7 m −1 • sr −1 . This phenomenon may be apparent for low particle backscatter conditions and larger instrumental noise [49].…”

Framework of Electric Vehicle Fault Diagnosis System Based on Diagnostic Communication

“…Simultaneously, the CAN layer furnishes 'Can_Cfg.h' to house configuration parameter information necessary during the pre-compilation phase. The specific services are then implemented in 'Can.c' (28).…”

Development of China’s first space-borne aerosol-cloud high-spectral-resolution lidar: retrieval algorithm and airborne demonstration

“…The iterative reconstruction method was used to retrieve the EC by Xiao et al [24]. The basic principle of the iterative reconstruction method is a) estimate the close numerical range of LR in different layers based on the Pre-retrieval results from Supplementary Information S1.…”

“…The ACDL scientific team has studied a variety of aspects about the retrieval algorithm for ACHSRL, starting from ground-based lidar, the error analysis of atmospheric parameters, the optimization design of iodine absorption cell, the calibration of overlap function, and the feature detection to the extinction coefficient retrieval [22][23][24][25][26]. Subsequently, Dong et al analyzed the optimum iodine absorption line of ACHSRL [27].…”