A method to tighten the cloud screening thresholds based on local conditions is used to provide more stringent schemes for Orbiting Carbon Observatory-2(OCO-2)cloud screening algorithms.Cloud screening strategies are ...A method to tighten the cloud screening thresholds based on local conditions is used to provide more stringent schemes for Orbiting Carbon Observatory-2(OCO-2)cloud screening algorithms.Cloud screening strategies are essential to remove scenes with significant cloud and/or aerosol contamination from OCO-2 observations,which helps to save on the data processing cost and ensure high quality retrievals of the column-averaged CO2 dry air mole fraction(XCO2).Based on the radiance measurements in the 0.76μm O2A band,1.61μm(weak),and 2.06μm(strong)CO2 bands,the current combination of the A-Band Preprocessor(ABP)algorithm and Iterative Maximum A Posteriori(IMAP)Differential Optical Absorption Spectroscopy(DOAS)Preprocessor(IDP)algorithm passes around 20%-25%of all soundings,which means that some contaminated scenes also pass the screening process.In this work,three independent pairs of threshold parameters used in the ABP and IDP algorithms are sufficiently tuned until the overall pass rate is close to the monthly clear-sky fraction from the MODIS cloud mask.The tightened thresholds are applied to observations over land surfaces in Europe and Japan in 2016.The results show improvement of agreement and positive predictive value compared to the collocated MODIS cloud mask,especially in summer and fall.In addition,analysis indicates that XCO2 retrievals with more stringent thresholds are in closer agreement with measurements from collocated Total Carbon Column Observing Network(TCCON)sites.展开更多
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the National Key Research Program of China(Grant No.2016YFC0200900)the National Natural Science Foundation of China(NSFC)(Grant No.41775023)+1 种基金the Excellent Young Scientists Program of the Zhejiang Provincial Natural Science Foundation of China(Grant No.LR19D050001)the Fundamental Research Funds for the Central Universities,and the State Key Laboratory of Modern Optical Instrumentation Innovation Program.
文摘A method to tighten the cloud screening thresholds based on local conditions is used to provide more stringent schemes for Orbiting Carbon Observatory-2(OCO-2)cloud screening algorithms.Cloud screening strategies are essential to remove scenes with significant cloud and/or aerosol contamination from OCO-2 observations,which helps to save on the data processing cost and ensure high quality retrievals of the column-averaged CO2 dry air mole fraction(XCO2).Based on the radiance measurements in the 0.76μm O2A band,1.61μm(weak),and 2.06μm(strong)CO2 bands,the current combination of the A-Band Preprocessor(ABP)algorithm and Iterative Maximum A Posteriori(IMAP)Differential Optical Absorption Spectroscopy(DOAS)Preprocessor(IDP)algorithm passes around 20%-25%of all soundings,which means that some contaminated scenes also pass the screening process.In this work,three independent pairs of threshold parameters used in the ABP and IDP algorithms are sufficiently tuned until the overall pass rate is close to the monthly clear-sky fraction from the MODIS cloud mask.The tightened thresholds are applied to observations over land surfaces in Europe and Japan in 2016.The results show improvement of agreement and positive predictive value compared to the collocated MODIS cloud mask,especially in summer and fall.In addition,analysis indicates that XCO2 retrievals with more stringent thresholds are in closer agreement with measurements from collocated Total Carbon Column Observing Network(TCCON)sites.
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.
