• DocumentCode
    962305
  • Title

    Inference of ice cloud properties from high spectral resolution infrared observations

  • Author

    Huang, Hung-Lung ; Yang, Ping ; Wei, Heli ; Baum, Bryan A. ; Hu, Yongxiang ; Antonelli, Paolo ; Ackerman, Steven A.

  • Author_Institution
    Cooperative Inst. for Meteorol. Satellite Studies, Univ. of Wisconsin, Madison, WI, USA
  • Volume
    42
  • Issue
    4
  • fYear
    2004
  • fDate
    4/1/2004 12:00:00 AM
  • Firstpage
    842
  • Lastpage
    853
  • Abstract
    The theoretical basis is explored for inferring the microphysical properties of ice clouds from high spectral resolution infrared (IR) observations. Extensive radiative transfer simulations are carried out to address relevant issues. The single-scattering properties of individual ice crystals are computed from state-of-the-art light scattering computational methods and are subsequently averaged for 30 in situ particle size distributions and for four additional analytical Gamma size distributions. The nonsphericity of ice crystals is shown to have a significant impact on the radiative signatures in the IR spectrum. Furthermore, the errors associated with the use of the Henyey-Greenstein phase function can be larger than 1 K in terms of brightness temperature for large particle effective sizes (∼80 μm) at wavenumbers where the scattering of the IR radiation by ice crystals is not negligible. The simulations undertaken in this paper show that the slope of the IR brightness temperature spectrum between 790-960 cm-1 is sensitive to the effective particle size. Furthermore, a strong sensitivity of the IR brightness temperature to cloud optical thickness is noted within the 1050-1250-cm-1 region. Based on these spectral features, a technique is presented for the simultaneous retrieval of the visible optical thickness and effective particle size from high spectral resolution IR data for ice clouds. An error analysis shows that the uncertainties of the retrieved optical thickness and effective particle size have a small range of variation. The error for retrieving particle size in conjunction with an uncertainty of 5 K in cloud temperature, or a surface temperature uncertainty of 2.5 K, is less than 15%. The corresponding errors in the uncertainty of optical thickness are within 5% to 20%, depending on the value of cloud optical thickness. The applicability of the present retrieval technique is demonstrated using airborne high-resolution IR measurements obtained during two field campaigns.
  • Keywords
    aerosols; atmospheric optics; atmospheric spectra; atmospheric techniques; clouds; ice; infrared imaging; radiative transfer; 1050 to 1250 cm-1; 790 to 960 cm-1; Henyey-Greenstein phase function; IR observations; IR radiation; IR spectrum; airborne high-resolution IR measurements; analytical Gamma size distributions; brightness temperature; cloud temperature; high spectral resolution infrared observations; ice cloud properties inference; ice crystal nonsphericity; infrared spectrum; light scattering computational methods; microphysical properties; particle effective sizes; particle size distributions; radiative signatures; radiative transfer simulations; sensitivity; single-scattering properties; spectral features; surface temperature; visible optical thickness; wavenumber; Brightness temperature; Clouds; Crystals; Distributed computing; Ice thickness; Infrared spectra; Light scattering; Optical scattering; Optical sensors; Uncertainty;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0196-2892
  • Type

    jour

  • DOI
    10.1109/TGRS.2003.822752
  • Filename
    1288378