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al. 2001 ). A failure to account for the additional depolarization induced by multiple scattering can introduce substantial uncertainties in cloud phase discrimination. In accounting for multiple scattering in ice clouds, it is convenient to assume that ice crystals have random orientations in radiative transfer and remote sensing studies. However, under conditions of weak updraft velocities, some types of ice cloud particles, such as columns and plates, appear to have preferred horizontal
al. 2001 ). A failure to account for the additional depolarization induced by multiple scattering can introduce substantial uncertainties in cloud phase discrimination. In accounting for multiple scattering in ice clouds, it is convenient to assume that ice crystals have random orientations in radiative transfer and remote sensing studies. However, under conditions of weak updraft velocities, some types of ice cloud particles, such as columns and plates, appear to have preferred horizontal
wavelengths in the 331–500-nm range and two wavelengths in the near UV—as two independent methods for making aerosol retrievals ( Torres et al. 2002 ). The OMI aerosol algorithm derives aerosol optical properties by comparing the measured reflectance to results from radiative transfer calculations of five major aerosol models: urban–industrial, biomass burning, desert dust, oceanic, and volcanic. These are further categorized into 24 subtypes by size distributions and refractive indices. Like the CALIPSO
wavelengths in the 331–500-nm range and two wavelengths in the near UV—as two independent methods for making aerosol retrievals ( Torres et al. 2002 ). The OMI aerosol algorithm derives aerosol optical properties by comparing the measured reflectance to results from radiative transfer calculations of five major aerosol models: urban–industrial, biomass burning, desert dust, oceanic, and volcanic. These are further categorized into 24 subtypes by size distributions and refractive indices. Like the CALIPSO
. , 2009 : CALIPSO lidar description and performance assessment. J. Atmos. Oceanic Technol. , 26 , 1214 – 1228 . 10.1175/2009JTECHA1223.1 Kay, S. M. , 1998 : Fundamentals of Statistical Signal Processing: Detection Theory . Prentice-Hall, 560 pp . Lane, D. E. , Goris K. , and Somerville R. C. J. , 2002 : Radiative transfer through broken clouds: Observations and model validation. J. Climate , 15 , 2921 – 2933 . 10.1175/1520-0442(2002)015<2921:RTTBCO>2.0.CO;2 Liu, Z. , and
. , 2009 : CALIPSO lidar description and performance assessment. J. Atmos. Oceanic Technol. , 26 , 1214 – 1228 . 10.1175/2009JTECHA1223.1 Kay, S. M. , 1998 : Fundamentals of Statistical Signal Processing: Detection Theory . Prentice-Hall, 560 pp . Lane, D. E. , Goris K. , and Somerville R. C. J. , 2002 : Radiative transfer through broken clouds: Observations and model validation. J. Climate , 15 , 2921 – 2933 . 10.1175/1520-0442(2002)015<2921:RTTBCO>2.0.CO;2 Liu, Z. , and
