Editorial Type:
Article
Article Type:
Research Article

An Effective Radius Retrieval for Thick Ice Clouds Using GOES

Daniel T. Lindsey Regional and Mesoscale Meteorology Branch, NOAA/NESDIS, Fort Collins, Colorado

Search for other papers by Daniel T. Lindsey in
Current site
Google Scholar
PubMed Close
and
Louie Grasso Cooperative Institute for Research in the Atmosphere, Fort Collins, Colorado

Search for other papers by Louie Grasso in
Current site
Google Scholar
PubMed Close
Print Publication:
01 Apr 2008
DOI:
https://doi.org/10.1175/2007JAMC1612.1
Page(s):
1222–1231
Restricted access

Abstract

Satellite retrieval of cirrus cloud microphysical properties is an important but difficult problem because of uncertainties in ice-scattering characteristics. Most methods have been developed for instruments aboard polar-orbiting satellites, which have better spatial and spectral resolution than geostationary sensors. The Geostationary Operational Environmental Satellite (GOES) series has the advantage of excellent temporal resolution, so that the evolution of thunderstorm-cloud-top properties can be monitored. In this paper, the authors discuss the development of a simple ice cloud effective radius retrieval for thick ice clouds using three bands from the GOES imager: one each in the visible, shortwave infrared, and window infrared portion of the spectrum. It is shown that this retrieval compares favorably to the MODIS effective radius algorithm. In addition, a comparison of the retrieval for clouds viewed simultaneously from GOES-East and GOES-West reveals that the assumed ice-scattering properties perform very well. The algorithm is then used to produce maps of mean ice cloud effective radius over the continental United States. A real-time version of this retrieval is currently running and may be used to study the evolution of thunderstorm-top ice crystal size in rapidly evolving convection.

Corresponding author address: Daniel T. Lindsey, CIRA/Colorado State University, 1375 Campus Delivery, Fort Collins, CO 80523-1375. Email: lindsey@cira.colostate.edu

Abstract

Satellite retrieval of cirrus cloud microphysical properties is an important but difficult problem because of uncertainties in ice-scattering characteristics. Most methods have been developed for instruments aboard polar-orbiting satellites, which have better spatial and spectral resolution than geostationary sensors. The Geostationary Operational Environmental Satellite (GOES) series has the advantage of excellent temporal resolution, so that the evolution of thunderstorm-cloud-top properties can be monitored. In this paper, the authors discuss the development of a simple ice cloud effective radius retrieval for thick ice clouds using three bands from the GOES imager: one each in the visible, shortwave infrared, and window infrared portion of the spectrum. It is shown that this retrieval compares favorably to the MODIS effective radius algorithm. In addition, a comparison of the retrieval for clouds viewed simultaneously from GOES-East and GOES-West reveals that the assumed ice-scattering properties perform very well. The algorithm is then used to produce maps of mean ice cloud effective radius over the continental United States. A real-time version of this retrieval is currently running and may be used to study the evolution of thunderstorm-top ice crystal size in rapidly evolving convection.

Corresponding author address: Daniel T. Lindsey, CIRA/Colorado State University, 1375 Campus Delivery, Fort Collins, CO 80523-1375. Email: lindsey@cira.colostate.edu

Save
Cover Journal of Applied Meteorology and Climatology
Journal of Applied Meteorology and Climatology

  • Baum, B. A., A. J. Heymsfield, P. Yang, and S. T. Bedka, 2005a: Bulk scattering properties for the remote sensing of ice clouds. Part I: Microphysical data and models. J. Appl. Meteor., 44 , 1885–1895.

    • Search Google Scholar
    • Export Citation

  • Baum, B. A., P. Yang, A. J. Heymsfield, S. Platnick, M. D. King, Y-X. Hu, and S. T. Bedka, 2005b: Bulk scattering properties for the remote sensing of ice clouds. Part II: Narrowband models. J. Appl. Meteor., 44 , 1896–1911.

    • Search Google Scholar
    • Export Citation

  • Cooper, S. J., T. S. L’Ecuyer, P. Gabriel, A. J. Baran, and G. L. Stephens, 2006: Objective assessment of the information content of visible and infrared radiance measurements for cloud microphysical property retrievals over the global oceans. Part II: Ice clouds. J. Appl. Meteor. Climatol., 45 , 42–62.

    • Search Google Scholar
    • Export Citation

  • Evans, K. F., 1998: The spherical harmonics discrete ordinate method for three-dimensional atmospheric radiative transfer. J. Atmos. Sci., 55 , 429–446.

    • Search Google Scholar
    • Export Citation

  • Grasso, L. D., and T. J. Greenwald, 2004: Analysis of 10.7-μm brightness temperatures of a simulated thunderstorm with two-moment microphysics. Mon. Wea. Rev., 132 , 815–825.

    • Search Google Scholar
    • Export Citation

  • Greenwald, T. J., R. Hertenstein, and T. Vukićević, 2002: An all-weather observational operator for radiance data assimilation with mesoscale forecast models. Mon. Wea. Rev., 130 , 1882–1897.

    • Search Google Scholar
    • Export Citation

  • Han, Q., W. B. Rossow, and A. A. Lacis, 1994: Near-global survey of effective droplet radii in liquid water clouds using ISCCP data. J. Climate, 7 , 465–497.

    • Search Google Scholar
    • Export Citation

  • Hillger, D. W., T. J. Schmit, and J. M. Daniels, 2003: Imager and sounder radiance and product validations for the. GOES-12 science test. NOAA Tech. Rep. NESDIS 115, 70 pp.

    • 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 , 442–458.

    • Search Google Scholar
    • Export Citation

  • Lindsey, D. T., D. W. Hillger, L. Grasso, J. A. Knaff, and J. F. Dostalek, 2006: GOES climatology and analysis of thunderstorms with enhanced 3.9-μm reflectivity. Mon. Wea. Rev., 134 , 2342–2353.

    • Search Google Scholar
    • Export Citation

  • Liou, K-N., 1986: Influence of cirrus clouds on weather and climate processes: A global perspective. Mon. Wea. Rev., 114 , 1167–1199.

  • McKague, D., and K. F. Evans, 2002: Multichannel satellite retrieval of cloud parameter probability distribution functions. J. Atmos. Sci., 59 , 1371–1382.

    • Search Google Scholar
    • Export Citation

  • Minnis, P., K-N. Liou, and Y. Takano, 1993: Inference of cirrus cloud properties using satellite-observed visible and infrared radiances. Part I: Parameterization of radiance fields. J. Atmos. Sci., 50 , 1279–1304.

    • Search Google Scholar
    • Export Citation

  • Nakajima, T., and M. D. King, 1990: Determination of the optical thickness and effective particle radius of clouds from reflected solar radiation measurements. Part I: Theory. J. Atmos. Sci., 47 , 1878–1893.

    • Search Google Scholar
    • Export Citation

  • Platnick, S., M. D. King, S. A. Ackerman, W. P. Menzel, B. A. Baum, J. C. Riédi, and R. A. Frey, 2003: The MODIS cloud products: Algorithms and examples from Terra. IEEE Trans. Geosci. Remote Sens., 41 , 459–473.

    • Search Google Scholar
    • Export Citation

  • Roebeling, R. A., A. J. Feijt, and P. Stammes, 2006: Cloud property retrievals for climate monitoring: Implications of differences between Spinning Enhanced Visible and Infrared Imager (SEVIRI) on METEOSAT-8 and Advanced Very High Resolution Radiometer (AVHRR) on NOAA-17. J. Geophys. Res., 111 .D20210, doi:10.1029/2005JD006990.

    • Search Google Scholar
    • Export Citation

  • Stamnes, K., S-C. Tsay, W. Wiscombe, and K. Jayaweera, 1988: Numerically stable algorithm for discrete-ordinate-method radiative transfer in multiple scattering and emitting layered media. Appl. Opt., 27 , 2502–2509.

    • Search Google Scholar
    • Export Citation

  • Stephens, G. L., S-C. Tsay, P. W. Stackhouse Jr., and P. J. Flatau, 1990: The relevance of the microphysical and radiative properties of cirrus clouds to climate and climatic feedback. J. Atmos. Sci., 47 , 1742–1753.

    • Search Google Scholar
    • Export Citation

  • Wetzel, M. A., R. D. Borys, and L. E. Xu, 1996: Satellite microphysical retrievals for land-based fog with validation by balloon profiling. J. Appl. Meteor., 35 , 810–829.

    • Search Google Scholar
    • Export Citation

  • Yang, P., K. N. Liou, K. Wyser, and D. Mitchell, 2000: Parameterization of the scattering and absorption properties of individual ice crystals. J. Geophys. Res., 105 , 4699–4718.

    • Search Google Scholar
    • Export Citation

  • Yang, P., B. A. Baum, A. J. Heymsfield, Y. X. Hu, H-L. Huang, S-C. Tsay, and S. Ackerman, 2003: Single-scattering properties of droxtals. J. Quant. Spectrosc. Radiat. Transfer, 79-80 , 1159–1169.

    • Search Google Scholar
    • Export Citation

  • Yang, P., H. Wei, H-L. Huang, B. A. Baum, Y. X. Hu, G. W. Kattawar, M. I. Mishchenko, and Q. Fu, 2005: Scattering and absorption property database for nonspherical ice particles in the near- through far-infrared spectral region. Appl. Opt., 44 , 5512–5523.

    • Search Google Scholar
    • Export Citation

  • Yang, P., L. Zhang, G. Hong, S. L. Nasiri, B. A. Baum, H-L. Huang, M. D. King, and S. Platnick, 2007: Differences between collection 4 and 5 MODIS ice cloud optical/microphysical products and their impact on radiative forcing simulations. IEEE Trans. Geosci. Remote Sens., 45 , 2886–2899.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 160 71 5
PDF Downloads 89 40 2