Aerosols and clouds greatly affect the Earth’s radiation budget and global climate.Light detection and ranging(lidar)has been recognized as a promising active remotesensing technique for the vertical observations of ...Aerosols and clouds greatly affect the Earth’s radiation budget and global climate.Light detection and ranging(lidar)has been recognized as a promising active remotesensing technique for the vertical observations of aerosols and clouds.China launchedits first space-borne aerosol-cloud high-spectral-resolution lidar(ACHSRL)on April 16,2022,which is capable for high accuracy profiling of aerosols and clouds around theglobe.This study presents a retrieval algorithm for aerosol and cloud optical propertiesfrom ACHSRL which were compared with the end-to-end Monte-Carlo simulationsand validated with the data from an airborne flight with the ACHSRL prototype(A2P)instrument.Using imaging denoising,threshold discrimination,and iterative reconstructionmethods,this algorithm was developed for calibration,feature detection,and extinction coefficient(EC)retrievals.The simulation results show that 95.4%of thebackscatter coefficient(BSC)have an error less than 12%while 95.4%of EC have anerror less than 24%.Cirrus and marine and urban aerosols were identified based on theairborne measurements over different surface types.Then,comparisons were madewith U.S.Cloud-Aerosol Lidar with Orthogonal Polarization(CALIOP)profiles,ModerateresolutionImaging Spectroradiometer(MODIS),and the ground-based sun photometers.High correlations(R>0.79)were found between BSC(EC)profiles of A2P andCALIOP over forest and town cover,while the correlation coefficients are 0.57 for BSCand 0.58 for EC over ocean cover;the aerosol optical depth retrievals have correlationcoefficient of 0.71 with MODIS data and show spatial variations consistent with thosefrom the sun photometers.The algorithm developed for ACHSRL in this study can bedirectly employed for future space-borne high-spectral-resolution lidar(HSRL)and itsdata products will also supplement CALIOP data coverage for global observations ofaerosol and cloud properties.展开更多
基金supported by the Excellent Young Scientist Program of Zhejiang Provincial Natural Science Foundation of China(LR19D050001)State Key Laboratory of Modern Optical Instrumentation Innovation Program(MOI2021ZD01)A Project Supported by Scientific Research Fund of Zhejiang University(XY2021050).
文摘Aerosols and clouds greatly affect the Earth’s radiation budget and global climate.Light detection and ranging(lidar)has been recognized as a promising active remotesensing technique for the vertical observations of aerosols and clouds.China launchedits first space-borne aerosol-cloud high-spectral-resolution lidar(ACHSRL)on April 16,2022,which is capable for high accuracy profiling of aerosols and clouds around theglobe.This study presents a retrieval algorithm for aerosol and cloud optical propertiesfrom ACHSRL which were compared with the end-to-end Monte-Carlo simulationsand validated with the data from an airborne flight with the ACHSRL prototype(A2P)instrument.Using imaging denoising,threshold discrimination,and iterative reconstructionmethods,this algorithm was developed for calibration,feature detection,and extinction coefficient(EC)retrievals.The simulation results show that 95.4%of thebackscatter coefficient(BSC)have an error less than 12%while 95.4%of EC have anerror less than 24%.Cirrus and marine and urban aerosols were identified based on theairborne measurements over different surface types.Then,comparisons were madewith U.S.Cloud-Aerosol Lidar with Orthogonal Polarization(CALIOP)profiles,ModerateresolutionImaging Spectroradiometer(MODIS),and the ground-based sun photometers.High correlations(R>0.79)were found between BSC(EC)profiles of A2P andCALIOP over forest and town cover,while the correlation coefficients are 0.57 for BSCand 0.58 for EC over ocean cover;the aerosol optical depth retrievals have correlationcoefficient of 0.71 with MODIS data and show spatial variations consistent with thosefrom the sun photometers.The algorithm developed for ACHSRL in this study can bedirectly employed for future space-borne high-spectral-resolution lidar(HSRL)and itsdata products will also supplement CALIOP data coverage for global observations ofaerosol and cloud properties.
