• Ackerman, S. A., W. L. Smith, J. D. Spinhirne, and H. E. Revercomb, 1990: The 27-28 October 1986 FIRE IFO cirrus case study: Spectral properties of cirrus clouds in the 8-12 μm window. Mon. Wea. Rev., 118 , 23772388.

    • Search Google Scholar
    • Export Citation
  • Ackerman, S. A., K. I. Strabala, W. P. Menzel, R. A. Frey, C. C. Moeller, and L. E. Gumley, 1998: Discriminating clear sky from clouds with MODIS. J. Geophys. Res., 103 , 3214132157.

    • Search Google Scholar
    • Export Citation
  • Ackerman, S. A., and Coauthors, 2006: Discriminating clear-sky from cloud with MODIS. Algorithm Theoretical Basis Doc. ATBD-MOD-06, NASA Goddard Space Flight Center, 35 pp.

  • Aumann, H. H., and Coauthors, 2003: AIRS/AMSU/HSB on the Aqua mission: Design, science objectives, data products, and processing systems. IEEE Trans. Geosci. Remote Sens., 41 , 253264.

    • Search Google Scholar
    • Export Citation
  • Baker, M. B., 1997: Cloud microphysics and climate. Science, 276 , 10721078.

  • Baran, A. J., 2003: Simulation of infrared scattering by ice aggregates by use of a size-shape distribution of circular ice cylinders. Appl. Opt., 42 , 28112818.

    • Search Google Scholar
    • Export Citation
  • Baran, A. J., S. Havemann, and D. Mackowski, 2002: A database of hexagonal column optical properties for wavelengths ranging between 0.2. μm and 30 μm produced for ANNEX 7. Contract 4b/3/02, Department for Environment, Food and Rural Affairs Rep., London, United Kingdom, 7 pp.

    • Search Google Scholar
    • Export Citation
  • Barnes, W. L., T. S. Pagano, and V. V. Salomonson, 1998: Prelaunch characteristics of the Moderate Resolution Imaging Spectroradiometer (MODIS) on EOS-AM1. IEEE Trans. Geosci. Remote Sens., 36 , 10881100.

    • Search Google Scholar
    • Export Citation
  • Baum, B. A., D. P. Kratz, P. Yang, S. C. Ou, Y. Hu, P. F. Soulen, and S-C. Tsay, 2000a: Remote sensing of cloud properties using MODIS Airborne Simulator imagery during SUCCESS 1. Data and models. J. Geophys. Res., 105 , 1176711780.

    • Search Google Scholar
    • Export Citation
  • Baum, B. A., P. F. Soulen, K. I. Strabala, M. D. King, S. A. Ackerman, W. P. Menzel, and P. Yang, 2000b: Remote sensing of cloud properties using MODIS Airborne Simulator imagery during SUCCESS 2. Cloud thermodynamic phase. J. Geophys. Res., 105 , 1178111792.

    • Search Google Scholar
    • Export Citation
  • Cess, R. D., and Coauthors, 1996: Cloud feedback in atmospheric general circulation models: An update. J. Geophys. Res., 101 , 1279112794.

    • Search Google Scholar
    • Export Citation
  • Chylek, P., and C. Borel, 2004: Mixed phase cloud water/ice structure from high spatial resolution satellite data. Geophys. Res. Lett., 31 .L14104, doi:10.1029/2004GL020428.

    • Search Google Scholar
    • Export Citation
  • Chylek, P., S. Robinson, M. K. Dubey, M. D. King, Q. Fu, and W. B. Clodius, 2006: Comparison of near-infrared and thermal infrared cloud phase detections. J. Geophys. Res., 111 .D20203, doi:10.1029/2006JD007140.

    • Search Google Scholar
    • Export Citation
  • Downing, H. D., and D. Williams, 1975: Optical constants of water in infrared. J. Geophys. Res., 80 , 16561661.

  • Harrison, E. F., P. Minnis, B. R. Barkstrom, V. Ramanathan, R. D. Cess, and G. G. Gibson, 1990: Seasonal variation of cloud radiative forcing derived from the Earth Radiation Budget Experiment. J. Geophys. Res., 95 , 1868718703.

    • Search Google Scholar
    • Export Citation
  • Houghton, J. T., Y. Ding, D. J. Griggs, M. Noguer, P. J. van der Linden, X. Dai, K. Maskell, and C. A. Johnson, 2001: Climate Change 2001: The Scientific Basis. Cambridge University Press, 881 pp.

    • Search Google Scholar
    • Export Citation
  • Kahn, B. H., and Coauthors, 2003: Near micron-sized cirrus cloud particles in high-resolution infrared spectra: An orographic case study. Geophys. Res. Lett., 30 .1441, doi:10.1029/2003GL016909.

    • Search Google Scholar
    • Export Citation
  • Kahn, B. H., and Coauthors, 2005: Nighttime cirrus detection using Atmospheric Infrared Sounder window channels and total column water vapor. J. Geophys. Res., 110 .D07203, doi:10.1029/2004JD005430.

    • Search Google Scholar
    • Export Citation
  • Kahn, B. H., E. Fishbein, S. L. Nasiri, A. Eldering, E. J. Fetzer, M. J. Garay, and S-Y. Lee, 2007: The radiative consistency of Atmospheric Infrared Sounder and Moderate Resolution Imaging Spectroradiometer cloud retrievals. J. Geophys. Res., 112 .D09201, doi:10.1029/2006JD007486.

    • Search Google Scholar
    • Export Citation
  • Kahn, B. H., C. K. Liang, A. Eldering, A. Gettelman, Q. Yue, and K. N. Liou, 2008: Tropical thin cirrus and relative humidity observed by the Atmospheric Infrared Sounder. Atmos. Chem. Phys., 8 , 15011518.

    • Search Google Scholar
    • Export Citation
  • Karl, T. R., and K. E. Trenberth, 2003: Modern global climate change. Science, 302 , 17191723.

  • Kaufman, Y. J., D. D. Herring, K. J. Ranson, and G. J. Collatz, 1998: Earth Observing System AM1 mission to Earth. IEEE Trans. Geosci. Remote Sens., 36 , 10451055.

    • Search Google Scholar
    • Export Citation
  • King, M. D., and Coauthors, 1996: Airborne scanning spectrometer for remote sensing of cloud, aerosol, water vapor, and surface properties. J. Atmos. Oceanic Technol., 13 , 777794.

    • Search Google Scholar
    • Export Citation
  • King, M. D., and Coauthors, 2003: Cloud and aerosol properties, precipitable water, and profiles of temperature and water vapor from MODIS. IEEE Trans. Geosci. Remote Sens., 41 , 442458.

    • Search Google Scholar
    • Export Citation
  • Knap, W. H., P. Stammes, and R. B. A. Koelemeijer, 2002: Cloud thermodynamic phase determination from near-infrared spectra of reflected sunlight. J. Atmos. Sci., 59 , 8396.

    • Search Google Scholar
    • Export Citation
  • Kokhanovsky, A. A., O. Jourdan, and J. P. Burrows, 2006: The cloud phase discrimination from a satellite. IEEE Geosci. Remote Sens. Lett., 3 , 103106.

    • Search Google Scholar
    • Export Citation
  • Kratz, D. P., 1995: The correlated k-distribution technique as applied to the AVHRR channels. J. Quant. Spectrosc. Radiat. Transfer, 53 , 501517.

    • Search Google Scholar
    • Export Citation
  • Li, J., and Coauthors, 2005: Retrieval of microphysical properties from MODIS and AIRS. J. Appl. Meteor., 44 , 15261543.

  • Menzel, W. P., B. A. Baum, K. I. Strabala, and R. A. Frey, 2002: Cloud top properties and cloud phase. MODIS Algorithm Theoretical Basis Doc. ATBD-MOD-04, NASA Goddard Space Flight Center, 61 pp.

  • Miles, N. L., J. Verlinde, and E. E. Clothiaux, 2000: Cloud droplet size distributions in low-level stratiform clouds. J. Atmos. Sci., 57 , 295311.

    • Search Google Scholar
    • Export Citation
  • Mishchenko, M. I., and L. D. Travis, 1998: Capabilities and limitations of a current FORTRAN implementation of the T-matrix method for randomly oriented, rotationally symmetric scatterers. J. Quant. Spectrosc. Radiat. Transfer, 60 , 309324.

    • Search Google Scholar
    • Export Citation
  • Moncet, J. L., and S. A. Clough, 1997: Accelerated monochromatic radiative transfer for scattering atmospheres: Application of a new model to spectral radiance observations. J. Geophys. Res., 102 , 2185321866.

    • Search Google Scholar
    • Export Citation
  • Nasiri, S. L., B. A. Baum, A. J. Heymsfield, P. Yang, M. R. Poellot, D. P. Kratz, and Y. Hu, 2002: The development of midlatitude cirrus models for MODIS using FIRE-I, FIRE-II, and ARM in situ data. J. Appl. Meteor., 41 , 197217.

    • Search Google Scholar
    • Export Citation
  • Niu, J., P. Yang, H. Huang, J. Davis, J. Li, B. Baum, and Y. Hu, 2007: A fast infrared radiative transfer model for overlapping clouds. J. Quant. Spectrosc. Radiat. Transfer, 103 , 447459.

    • Search Google Scholar
    • Export Citation
  • Norris, J. R., and C. P. Weaver, 2001: Improved techniques for evaluating GCM cloudiness applied to the NCAR CCM3. J. Climate, 14 , 25402550.

    • Search Google Scholar
    • Export Citation
  • Parkinson, C. L., 2003: Aqua: An earth-observing satellite mission to examine water and other climate variables. IEEE Trans. Geosci. Remote Sens., 41 , 173183.

    • Search Google Scholar
    • Export Citation
  • Pavolonis, M. J., A. K. Heidinger, and T. Uttal, 2005: Daytime global cloud typing from AVHRR and VIIRS: Algorithm description, validation, and comparisons. J. Appl. Meteor., 44 , 804826.

    • Search Google Scholar
    • Export Citation
  • Pilewskie, P., and S. Twomey, 1987: Cloud phase discrimination by reflectance measurements near 1.6 and 2.2 μm. J. Atmos. Sci., 44 , 34193420.

    • Search Google Scholar
    • Export Citation
  • Platnick, S., M. D. King, S. A. Ackerman, W. P. Menzel, B. A. Baum, and R. A. Frey, 2003: The MODIS cloud products: Algorithms and examples from Terra. IEEE Trans. Geosci. Remote Sens., 41 , 459473.

    • Search Google Scholar
    • Export Citation
  • Ramanathan, V., R. D. Cess, E. F. Harrison, P. Minnis, B. R. Barkstrom, E. Ahmad, and D. Hartmann, 1989: Cloud-radiative forcing and climate: Results from the Earth Radiation Budget Experiment. Science, 243 , 5763.

    • Search Google Scholar
    • Export Citation
  • Randall, D., and Coauthors, 2003: Confronting models with data: The GEWEX Cloud Systems Study. Bull. Amer. Meteor. Soc., 84 , 455469.

  • Riedi, J., M. Doutriaux-Boucher, P. Goloub, and P. Couvert, 2000: Global distribution of cloud top phase from POLDER/ADEOS I. Geophys. Res. Lett., 27 , 17071710.

    • Search Google Scholar
    • Export Citation
  • Rossow, W. B., and A. A. Lacis, 1990: Global, seasonal cloud variations from satellite radiance measurements. Part II: Cloud properties and radiative effects. J. Climate, 3 , 12041253.

    • Search Google Scholar
    • Export Citation
  • Rossow, W. B., and R. A. Schiffer, 1999: Advances in understanding clouds from ISCCP. Bull. Amer. Meteor. Soc., 80 , 22612287.

  • Smith, W. L., H. E. Revercomb, R. O. Knuteson, F. A. Best, R. Dedecker, H. B. Howell, and H. M. Woolf, 1995: Cirrus cloud properties derived from high spectral resolution infrared spectrometry during FIRE II. Part I: The High Resolution Interferometer Sounder (HIS) system. J. Atmos. Sci., 52 , 42394245.

    • Search Google Scholar
    • Export Citation
  • Stephens, G. L., 2005: Cloud feedbacks in the climate system: A critical review. J. Climate, 18 , 237273.

  • Strabala, K. I., S. A. Ackerman, and W. P. Menzel, 1994: Cloud properties inferred from 8–12-μm data. J. Appl. Meteor., 33 , 212229.

    • Search Google Scholar
    • Export Citation
  • Tobin, D. C., H. E. Revercomb, C. C. Moeller, and T. S. Pagano, 2006: Use of Atmospheric Infrared Sounder high-spectral resolution spectra to assess the calibration to Moderate Resolution Imaging Spectroradiometer on EOS Aqua. J. Geophys. Res., 111 .D09S05, doi:10.1029/2005JD006095.

    • Search Google Scholar
    • Export Citation
  • Tsay, S-C., K. Stamnes, and K. Jayaweera, 1990: Radiative transfer in stratified atmospheres: Development and verification of a unified model. J. Quant. Spectrosc. Radiat. Transfer, 43 , 133148.

    • Search Google Scholar
    • Export Citation
  • Warren, S. G., 1984: Optical constants of ice from the ultraviolet to the microwave. Appl. Opt., 23 , 12061225.

  • Wei, H., P. Yang, J. Li, B. A. Baum, H-L. Huang, S. Platnick, Y. Hu, and L. Strow, 2004: Retrieval of semitransparent ice cloud optical thickness from Atmospheric Infrared Sounder (AIRS) measurements. IEEE Trans. Geosci. Remote Sens., 42 , 22542267.

    • Search Google Scholar
    • Export Citation
  • Wielicki, B. A., R. D. Cess, M. D. King, D. A. Randall, and E. F. Harrison, 1995: Mission to planet Earth: Role of clouds and radiation in climate. Bull. Amer. Meteor. Soc., 76 , 21252153.

    • Search Google Scholar
    • Export Citation
  • Wielicki, B. A., and Coauthors, 2002: Evidence for large decadal variability in the tropical mean radiative energy budget. Science, 295 , 841844.

    • Search Google Scholar
    • Export Citation
  • Wylie, D. P., W. P. Menzel, H. M. Woolf, and K. I. Strabala, 1994: Four years of global cloud statistics using HIRS. J. Climate, 7 , 19721986.

    • Search Google Scholar
    • Export Citation
  • Wylie, D. P., D. L. Jackson, W. P. Menzel, and J. J. Bates, 2005: Trends in global cloud cover in two decades of HIRS observations. J. Climate, 18 , 30213031.

    • Search Google Scholar
    • Export Citation
  • Yang, P., H-L. Wei, B. A. Baum, H-L. Huang, A. J. Heymsfield, Y. X. Hu, B-C. Gao, and D. D. Turner, 2003: The spectral signature of mixed-phase clouds composed of nonspherical ice crystals and spherical liquid droplets in the terrestrial window region. J. Quant. Spectrosc. Radiat. Transfer, 79–80 , 11711188.

    • Search Google Scholar
    • Export Citation
  • Yue, Q., K. N. Liou, S. C. Ou, B. H. Kahn, P. Yang, and G. G. Mace, 2007: Interpretation of AIRS data in thin cirrus atmospheres based on a fast radiative transfer model. J. Atmos. Sci., 64 , 38273842.

    • Search Google Scholar
    • Export Citation
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Limitations of Bispectral Infrared Cloud Phase Determination and Potential for Improvement

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  • 1 Department of Atmospheric Sciences, Texas A&M University, College Station, Texas
  • | 2 Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California
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Abstract

Determining cloud thermodynamic phase using infrared satellite observations typically requires a priori assumptions about relationships between cloud phase and cloud temperature. In this study, limitations of an approach using two infrared channels with moderate spectral resolutions are demonstrated, as well as the potential for improvement using channels with higher spectral resolution. The Moderate Resolution Imaging Spectroradiometer (MODIS) instrument uses a bispectral infrared cloud phase determination algorithm. MODIS observations during January 2005 show that approximately 23% of cloudy pixels are classified as mixed or unknown cloud phase; this increases to 78% when only cloud-top temperatures between 250 and 265 K are considered. Radiative transfer simulations show that the bispectral algorithm has limited ability to discriminate between water and ice clouds in this temperature range. There is also the potential for thin ice clouds at colder temperatures to be misclassified as water clouds. In addition, sensitivities to cloud particle size and cloud height can be larger than sensitivities to cloud phase. Simulations suggest that phase sensitivity may be higher with hyperspectral observations such as those from the Atmospheric Infrared Sounder (AIRS). The AIRS brightness temperature differences between channels at 8.1 and 10.4 μm show phase sensitivities of at least 0.5 K, regardless of cloud particle size, cloud-top temperature, or cloud height. They also demonstrate reduced sensitivity to atmospheric temperature and water vapor variability. The reduced sensitivity of AIRS radiances to these physical quantities shows that hyperspectral sounders will serve an important role in refining estimates of cloud phase.

Corresponding author address: Shaima L. Nasiri, Dept. of Atmospheric Sciences, Texas A&M University, 3150 TAMU, College Station, TX 77843-3150. Email: snasiri@tamu.edu

Abstract

Determining cloud thermodynamic phase using infrared satellite observations typically requires a priori assumptions about relationships between cloud phase and cloud temperature. In this study, limitations of an approach using two infrared channels with moderate spectral resolutions are demonstrated, as well as the potential for improvement using channels with higher spectral resolution. The Moderate Resolution Imaging Spectroradiometer (MODIS) instrument uses a bispectral infrared cloud phase determination algorithm. MODIS observations during January 2005 show that approximately 23% of cloudy pixels are classified as mixed or unknown cloud phase; this increases to 78% when only cloud-top temperatures between 250 and 265 K are considered. Radiative transfer simulations show that the bispectral algorithm has limited ability to discriminate between water and ice clouds in this temperature range. There is also the potential for thin ice clouds at colder temperatures to be misclassified as water clouds. In addition, sensitivities to cloud particle size and cloud height can be larger than sensitivities to cloud phase. Simulations suggest that phase sensitivity may be higher with hyperspectral observations such as those from the Atmospheric Infrared Sounder (AIRS). The AIRS brightness temperature differences between channels at 8.1 and 10.4 μm show phase sensitivities of at least 0.5 K, regardless of cloud particle size, cloud-top temperature, or cloud height. They also demonstrate reduced sensitivity to atmospheric temperature and water vapor variability. The reduced sensitivity of AIRS radiances to these physical quantities shows that hyperspectral sounders will serve an important role in refining estimates of cloud phase.

Corresponding author address: Shaima L. Nasiri, Dept. of Atmospheric Sciences, Texas A&M University, 3150 TAMU, College Station, TX 77843-3150. Email: snasiri@tamu.edu

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