• Laser & Optoelectronics Progress
  • Vol. 59, Issue 10, 1028001 (2022)
Shujun Liao1、2, Haiyang Gao1、2、*, Leilei Kou1、2, Jiahui Kang2, Lingbing Bu1、2, and Zhen Wang1、2
Author Affiliations
  • 1Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science & Technology, Nanjing 210044, Jiangsu , China
  • 2School of Atmospheric Physics, Nanjing University of Information Science & Technology, Nanjing 210044, Jiangsu , China
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    DOI: 10.3788/LOP202259.1028001 Cite this Article Set citation alerts
    Shujun Liao, Haiyang Gao, Leilei Kou, Jiahui Kang, Lingbing Bu, Zhen Wang. Simulation of Cloud and Aerosol Detection Based on Spaceborne Lidar[J]. Laser & Optoelectronics Progress, 2022, 59(10): 1028001 Copy Citation Text show less
    Sub-module structure and logic framework of the forward model
    Fig. 1. Sub-module structure and logic framework of the forward model
    Spatiotemporal matching between CALIPSO and WRF data
    Fig. 2. Spatiotemporal matching between CALIPSO and WRF data
    Optical properties and scattering phase functions of three types of particles. (a) Optical property of ice crystal; (b) scattering phase function of ice crystal; (c) optical property of liquid water particle; (d) scattering phase function of liquid water particle; (e) optical property of aerosol; (f) scattering phase function of aerosol
    Fig. 3. Optical properties and scattering phase functions of three types of particles. (a) Optical property of ice crystal; (b) scattering phase function of ice crystal; (c) optical property of liquid water particle; (d) scattering phase function of liquid water particle; (e) optical property of aerosol; (f) scattering phase function of aerosol
    Deep convection scene simulation. (a) WRF simulation area; (b) layered distribution of ice and cloud water mixing ratio
    Fig. 4. Deep convection scene simulation. (a) WRF simulation area; (b) layered distribution of ice and cloud water mixing ratio
    Deep convection scene simulation. (a) Ice and water content; (b) backscattering coefficient; (c) attenuation coefficient; (d) attenuated backscattering coefficient; (e) simulation signal; (f) signal-to-noise ratio
    Fig. 5. Deep convection scene simulation. (a) Ice and water content; (b) backscattering coefficient; (c) attenuation coefficient; (d) attenuated backscattering coefficient; (e) simulation signal; (f) signal-to-noise ratio
    Ice cloud and aerosol scene simulation. (a) WRF simulation area; (b) layered distribution of ice water content and aerosol dry mass
    Fig. 6. Ice cloud and aerosol scene simulation. (a) WRF simulation area; (b) layered distribution of ice water content and aerosol dry mass
    Ice cloud and aerosol scene simulation. (a) aerosol content and ice water content; (b) backscattering coefficient; (c) attenuation coefficient; (d) attenuated backscattering coefficient; (e) simulation signal; (f) signal-to-noise ratio
    Fig. 7. Ice cloud and aerosol scene simulation. (a) aerosol content and ice water content; (b) backscattering coefficient; (c) attenuation coefficient; (d) attenuated backscattering coefficient; (e) simulation signal; (f) signal-to-noise ratio
    Sensitivity analysis in aerosol scene. (a) Simulation signal; (b) signal-to-noise ratio
    Fig. 8. Sensitivity analysis in aerosol scene. (a) Simulation signal; (b) signal-to-noise ratio
    Influence of three parameters on the SNR of simulation signal. (a) Influence of Zsat on SNR; (b) influence of three Zsat on SNR at different altitudes; (c) influence of three altitudes on SNR under different Zsat; (d) influence of Dtel on SNR; (e) influence of three Dtel on SNR at different altitudes; (f) influence of three altitudes on SNR under different Dtel; (g) influence of E on SNR; (h) influence of three E on SNR at different altitudes; (i) influence of three altitudes on SNR under different E
    Fig. 9. Influence of three parameters on the SNR of simulation signal. (a) Influence of Zsat on SNR; (b) influence of three Zsat on SNR at different altitudes; (c) influence of three altitudes on SNR under different Zsat; (d) influence of Dtel on SNR; (e) influence of three Dtel on SNR at different altitudes; (f) influence of three altitudes on SNR under different Dtel; (g) influence of E on SNR; (h) influence of three E on SNR at different altitudes; (i) influence of three altitudes on SNR under different E
    Influence of two PSD on simulation signal. (a) Simulation signal of Gamma PSD; (b) simulation signal of Modified Gamma PSD; (c) comparison of two PSD simulation signals at three different latitudes; (d) difference of PSD simulation signals at three different latitudes
    Fig. 10. Influence of two PSD on simulation signal. (a) Simulation signal of Gamma PSD; (b) simulation signal of Modified Gamma PSD; (c) comparison of two PSD simulation signals at three different latitudes; (d) difference of PSD simulation signals at three different latitudes
    Comparison of attenuated backscattering coefficient. (a) Attenuated backscattering coefficient of CALIPSO Level 1 data; (b) ice water content of CALIPSO Level 2 data; (c) attenuated backscattering coefficient simulated by the forward model; (d) comparison of the average value between the Level 1 data and the simulated backscattering coefficient
    Fig. 11. Comparison of attenuated backscattering coefficient. (a) Attenuated backscattering coefficient of CALIPSO Level 1 data; (b) ice water content of CALIPSO Level 2 data; (c) attenuated backscattering coefficient simulated by the forward model; (d) comparison of the average value between the Level 1 data and the simulated backscattering coefficient
    TypeParameterSymbolUnit
    HydrometeorMixing ratio of cloud/ice/rain/snow/graupel

    QCLOUD/QICE/QRAIN/

    QSNOW/GRAUPEL

    kg·kg-1
    AerosolDry mass of PM10PM10μg·m3
    Dry mass of PM2.5PM2.5
    Table 1. Parameters of hydrometeor and aerosol in WRF and WRF-CHEM
    SymbolParameterValue(example)
    Zsat /kmSatellite orbit altitude705
    Dtel /mTelescope diameter1.0
    TsysOptical system transmittance0.14
    ηQuantum efficiency of PMT photocathode0.25@532 nm
    GPMTphotoelectron gain coefficient5×106
    CaduDigital to analog conversion coefficient1/1000
    E /mJLaser single pulse energy150
    Table 2. Some important instrument parameters
    Altitude region /kmVertical resolution /mHorizontal resolution /kmSamples per profile
    30.1-40.03005.033
    20.2-30.11805/355
    8.2-20.2601.0200
    -0.5-8.2301/3290
    -2--0.53001/35
    Table 3. Spatial resolution of CALIPSO Level 1B data
    Shujun Liao, Haiyang Gao, Leilei Kou, Jiahui Kang, Lingbing Bu, Zhen Wang. Simulation of Cloud and Aerosol Detection Based on Spaceborne Lidar[J]. Laser & Optoelectronics Progress, 2022, 59(10): 1028001
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