Stratiform and Convective Classification of Rainfall Using SSM/I 85-GHz Brightness Temperature Observations

Emmanouil N. Anagnostou Department of Civil and Environmental Engineering and Iowa Institute of Hydraulic Research, University of Iowa, Iowa City, Iowa

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Christian Kummerow Mesoscale Atmospheric Processes Branch, Goddard Space Flight Center, National Aeronautics and Space Administration, Greenbelt, Maryland

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Abstract

A better understanding of global climate calls for more accurate estimates of liquid and ice water content profiles of precipitating clouds and their associated latent heating profiles. Convective and stratiform precipitation regimes have different latent heating and therefore impact the earth’s climate differently. Classification of clouds over oceans has traditionally been part of more general rainfall retrieval schemes. These schemes are based on individual or combined visible and infrared, and microwave satellite observations. However, none of these schemes report validations of their cloud classification with independent ground observations. The objective of this study is to develop a scheme to classify convective and stratiform precipitating clouds using satellite brightness temperature observations. The proposed scheme probabilistically relates a quantity called variability index (VI) to the stratiform fractional precipitation coverage over the satellite field of view (FOV). The VI for a satellite pixel is the mean absolute 85-GHz brightness temperature difference between the pixel and the eight surrounding neighbor pixels. The classification scheme has been applied to four different rainfall regimes. All four regimes show that the frequency of stratiform rainfall in the satellite FOV increases as the satellite-based VI decreases. The results of this study demonstrate that the satellite-based VI is consistently related to the probability of occurrence of three classes (0%–40%, 40%–70%, and 70%–100%) of FOV stratiform coverage.

Corresponding author address: Emmanouil N. Anagnostou, Institute of Hydraulic Research, University of Iowa, 404 Hydraulic Laboratory, Iowa City, IA 52242-1585.

Email: eocnagnos@iihr.uiowa.edu

Abstract

A better understanding of global climate calls for more accurate estimates of liquid and ice water content profiles of precipitating clouds and their associated latent heating profiles. Convective and stratiform precipitation regimes have different latent heating and therefore impact the earth’s climate differently. Classification of clouds over oceans has traditionally been part of more general rainfall retrieval schemes. These schemes are based on individual or combined visible and infrared, and microwave satellite observations. However, none of these schemes report validations of their cloud classification with independent ground observations. The objective of this study is to develop a scheme to classify convective and stratiform precipitating clouds using satellite brightness temperature observations. The proposed scheme probabilistically relates a quantity called variability index (VI) to the stratiform fractional precipitation coverage over the satellite field of view (FOV). The VI for a satellite pixel is the mean absolute 85-GHz brightness temperature difference between the pixel and the eight surrounding neighbor pixels. The classification scheme has been applied to four different rainfall regimes. All four regimes show that the frequency of stratiform rainfall in the satellite FOV increases as the satellite-based VI decreases. The results of this study demonstrate that the satellite-based VI is consistently related to the probability of occurrence of three classes (0%–40%, 40%–70%, and 70%–100%) of FOV stratiform coverage.

Corresponding author address: Emmanouil N. Anagnostou, Institute of Hydraulic Research, University of Iowa, 404 Hydraulic Laboratory, Iowa City, IA 52242-1585.

Email: eocnagnos@iihr.uiowa.edu

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  • Alishouse, J. C., J. B. Snider, E. R. Westwater, C. T. Swift, C. S. Ruf, S. A. Snyder, J. Vongsathorn, and R. R. Ferraro, 1990: Determination of cloud liquid water content using SSM/I. IEEE Trans. Geosci. Remote Sens.,28, 817–822.

    • Crossref
    • Export Citation
  • Bell, T. L., A. Abdullah, L. M. Russell, and G. R. North, 1990: Sampling errors for satellite-derived tropical rainfall: Monte Carlo study using a space–time stochastic model. J. Geophys. Res.,95, 2195–2205.

    • Crossref
    • Export Citation
  • Chiu, L. S., G. R. North, and D. A. Short, 1988: Errors in satellite rainfall estimation due to nonuniform field of view of space-borne microwave sensors. Proc. IUGG Conf. on Microwave Remote Sensing, Hampton, VA, Int. Union Geodesy Geophys.

  • Ciach, G. J., W. F. Krajewski, E. N. Anagnostou, M. L. Baeck, J. R. McCollum, A. Kruger, and J. A. Smith, 1997: Radar rainfall estimation for ground validation studies of the tropical rainfall measuring mission. J. Appl. Meteor.,36, 735–747.

    • Crossref
    • Export Citation
  • Greenwald, T. J., G. L. Stephens, T. H. Vonder Haar, and D. L. Jackson, 1993: A physical retrieval of cloud liquid water over the global oceans using Special Sensor Microwave/Imager (SSM/I) observations. J. Geophys. Res.,98, 18 471–18 488.

    • Crossref
    • Export Citation
  • Houze, R. A., 1993: Cloud Dynamics. Academic Press, 573 pp.

  • Inoue, T., 1987: A cloud type classification with NOAA 7 split-window measurements. J. Geophys. Res.,92, 3991–4000.

    • Crossref
    • Export Citation
  • Liu, G., and J. A. Curry, 1992: Retrieval of precipitation from satellite microwave measurement using both emission and scattering. J. Geophys. Res.,97, 9959–9974.

    • Crossref
    • Export Citation
  • ———, and ———, 1993: Determination of characteristic features of cloud liquid water from satellite microwave measurements. J. Geophys. Res.,98, 5069–5092.

    • Crossref
    • Export Citation
  • ———, ———, and R.-S. Sheu, 1995: Classification of clouds over the western equatorial Pacific Ocean using combined infrared and microwave satellite data. J. Geophys. Res.,100, 13 811–13 826.

  • McConnell, A., and G. R. North, 1987: Sampling errors in satellite estimates of tropical rain. J. Geophys. Res.,92, 9567–9570.

    • Crossref
    • Export Citation
  • Mitchell, J. F. B., C. A. Senior, and W. J. Ingram, 1989: C02 and climate: A missing feedback? Nature,341, 132–134.

  • Petty, G. W., 1990: On the response of the Special Sensor Microwave/Imager to marine environment—Implications for atmospheric parameter retrievals. Ph.D. dissertation, University of Washington, 291 pp.

  • Reynolds, D. W., and T. H. Vonder Haar, 1977: A bispectral method for cloud parameter determination. Mon. Wea. Rev.,105, 446–457.

    • Crossref
    • Export Citation
  • Rossow, W. B., and R. A. Schiffer, 1991: ISCCP cloud data products. Bull. Amer. Meteor. Soc.,72, 2–20.

    • Crossref
    • Export Citation
  • Shenk, W. E., R. J. Holub, and R. A. Neff, 1976: A multispectral cloud type identification method using Nimbus-3 MRIR measurements. Mon. Wea. Rev.,104, 284–291.

    • Crossref
    • Export Citation
  • Shin, K.-S., and G. R. North, 1988: Sampling error study for rainfall estimate by satellite using a stochastic model. J. Appl. Meteor.,27, 1218–1231.

    • Crossref
    • Export Citation
  • Short, D. A., and G. R. North, 1990: The beam filling error in the Nimbus 5 electronically scanning microwave radiometer observations of Global Atlantic Tropical Experiment rainfall. J. Geophys. Res.,95, 2187–2193.

    • Crossref
    • Export Citation
  • Simpson, J., R. F. Adler, and G. R. North, 1988: A proposed Tropical Rainfall Measuring Mission (TRMM) satellite. Bull. Amer. Meteor. Soc.,69, 278–295.

    • Crossref
    • Export Citation
  • Steiner, M., R. A. Houze, and S. E. Yuter, 1995: Climatological characterization of three-dimensional storm structure from operational radar and rain gauge data. J. Appl. Meteor.,34, 1978–2007.

    • Crossref
    • Export Citation
  • Tao, W.-K., S. Lang, J. Simpson, and R. Adler, 1993a: Retrieval algorithms for estimating the vertical profiles of latent heat release: Their applications for TRMM. J. Meteor. Soc. Japan,71, 685–700.

    • Crossref
    • Export Citation
  • ———, J. Simpson, C.-H. Sui, S. Lang, J. Scala, B. Ferrier, M.-D. Chou, and K. Pickering, 1993b: Heating, moisture, and water budgets of tropical and midlatitude squall lines: Comparisons and sensitivity to longwave radiation. J. Atmos. Sci.,50, 673–690.

    • Crossref
    • Export Citation
  • Webster, P. J., and R. Lukas, 1992: TOGA COARE: The Coupled Ocean–Atmosphere Response Experiment. Bull. Amer. Meteor. Soc.,73, 1377–1416.

    • Crossref
    • Export Citation
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