Comparison of Two Convective/Stratiform Precipitation Classification Techniques: Radar Reflectivity Texture versus Drop Size Distribution–Based Approach

Guillaume Penide Laboratoire d'Optique Atmosphérique, UMR CNRS 8518, Université des Sciences et Technologies de Lille, Villeneuve d'Ascq, France

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Alain Protat Centre for Australian Weather and Climate Research, Melbourne, Victoria, Australia

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Vickal V. Kumar Centre for Australian Weather and Climate Research, Melbourne, and School of Mathematical Sciences, Monash University, Clayton, Victoria, Australia

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Peter T. May Centre for Australian Weather and Climate Research, Melbourne, Victoria, Australia

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Abstract

C-band polarimetric radar measurements spanning two wet seasons are used to perform a critical evaluation of two algorithms for the classification of stratiform and convective precipitation. The first approach is based on the horizontal texture of the radar reflectivity field (two classes: stratiform, convective), and the second approach is based on the properties of the drop size distribution (DSD) parameters as derived from a set of polarimetric variables (three classes: stratiform, mixed, convective). To investigate how well those two methods compare quantitatively, probability density functions of reflectivity, rain rate, 5-dBZ echo top height, and DSD parameters (namely, the median volume diameter and the “generalized” intercept parameter) are built. The study found that while the two methods agree well on the identification of stratiform precipitation, large differences are obtained for convective rainfall. The texture-based approach seems to classify too many points as being of convective nature compared to the DSD-based method. Among the points that are classified as convective by the texture-based approach, 25% correspond to low concentration of relatively small particles associated with rain rates below 10 mm h−1. This large proportion of unrealistically low convective rain rates is not produced by the DSD-based approach, which only classifies 4% of the convective points with rain rates below 10 mm h−1. These points were found to be mainly isolated points embedded within stratiform precipitation and associated with low cloud-top height, suggesting a misclassification of the texture-based approach. Thus, to improve the statistics of the convective class, three modified equations of the peakedness criterion used in the radar-based algorithm are proposed to decrease the number of misclassified points.

Corresponding author address: Guillaume Penide, Laboratoire d'Optique Atmosphérique, UMR CNRS 8518, Université Lille 1, 59655 Villeneuve d'Ascq CEDEX, France. E-mail: guillaume.penide@univ-lille1.fr

Abstract

C-band polarimetric radar measurements spanning two wet seasons are used to perform a critical evaluation of two algorithms for the classification of stratiform and convective precipitation. The first approach is based on the horizontal texture of the radar reflectivity field (two classes: stratiform, convective), and the second approach is based on the properties of the drop size distribution (DSD) parameters as derived from a set of polarimetric variables (three classes: stratiform, mixed, convective). To investigate how well those two methods compare quantitatively, probability density functions of reflectivity, rain rate, 5-dBZ echo top height, and DSD parameters (namely, the median volume diameter and the “generalized” intercept parameter) are built. The study found that while the two methods agree well on the identification of stratiform precipitation, large differences are obtained for convective rainfall. The texture-based approach seems to classify too many points as being of convective nature compared to the DSD-based method. Among the points that are classified as convective by the texture-based approach, 25% correspond to low concentration of relatively small particles associated with rain rates below 10 mm h−1. This large proportion of unrealistically low convective rain rates is not produced by the DSD-based approach, which only classifies 4% of the convective points with rain rates below 10 mm h−1. These points were found to be mainly isolated points embedded within stratiform precipitation and associated with low cloud-top height, suggesting a misclassification of the texture-based approach. Thus, to improve the statistics of the convective class, three modified equations of the peakedness criterion used in the radar-based algorithm are proposed to decrease the number of misclassified points.

Corresponding author address: Guillaume Penide, Laboratoire d'Optique Atmosphérique, UMR CNRS 8518, Université Lille 1, 59655 Villeneuve d'Ascq CEDEX, France. E-mail: guillaume.penide@univ-lille1.fr
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  • Adler, R. F., and Negri A. J. , 1988: A satellite infrared technique to estimate tropical convective and stratiform rainfall. J. Appl. Meteor., 27, 3051.

    • Search Google Scholar
    • Export Citation
  • Anagnostou, E. N., and Kummerov C. D. , 1997: Stratiform and convective classification of rainfall using SSM/I 85-GHz brightness temperature observations. J. Atmos. Oceanic Technol., 14, 570575.

    • Search Google Scholar
    • Export Citation
  • Biggerstaff, M. I., and Listemaa S. A. , 2000: An improved scheme for convective/stratiform echo classification using radar reflectivity. J. Appl. Meteor., 39, 21292149.

    • Search Google Scholar
    • Export Citation
  • Bringi, V. N., Keenan T. D. , and Chandrasekar V. , 2001: Correcting C-band radar reflectivity and differential reflectivity data for rain attenuation: A self-consistent method with constraints. IEEE Trans. Geosci. Remote Sens., 39, 19061915.

    • Search Google Scholar
    • Export Citation
  • Bringi, V. N., Williams C. R. , Thurai M. , and May P. T. , 2009: Using dual-polarized radar and dual-frequency profiler for DSD characterization: A case study from Darwin, Australia. J. Atmos. Oceanic Technol., 26, 21072122.

    • Search Google Scholar
    • Export Citation
  • Hong, Y., Kummerov C. D. , and Olson W. S. , 1999: Separation of convective and stratiform precipitation using microwave brightness temperature. J. Appl. Meteor., 38, 11951213.

    • Search Google Scholar
    • Export Citation
  • Houze, R. L., 1997: Stratiform precipitation in regions of convection: A meteorological paradox? Bull. Amer. Meteor. Soc., 78, 21792196.

    • Search Google Scholar
    • Export Citation
  • Hubbert, J., and Bringi V. N. , 1995: An iterative filtering technique for the analysis of copolar differential phase and dual-frequency radar measurements. J. Atmos. Oceanic Technol., 12, 643648.

    • Search Google Scholar
    • Export Citation
  • Johnson, R. H., Rickenbach T. M. , Rutledge S. A. , Ciesielski P. E. , and Schubert W. H. , 1999: Trimodal characteristics of tropical convection. J. Climate, 12, 23972418.

    • Search Google Scholar
    • Export Citation
  • Keenan, T., Glasson K. , Cummings F. , Bird T. S. , Keeler J. , and Lutz J. , 1998: The BMRC/NCAR C-band polarimetric (C-POL) radar system. J. Atmos. Oceanic Technol., 15, 871886.

    • Search Google Scholar
    • Export Citation
  • Kumar, V. V., Protat A. , May P. T. , Jacob C. , Penide G. , Kumar S. , and Davies L. , 2013: On the effects of large-scale environment and surface types on convective cloud characteristics over Darwin, Australia. Mon. Wea. Rev., 141, 1358–1374.

    • Search Google Scholar
    • Export Citation
  • Leary, C. A., and Houze R. A. Jr., 1979: Melting and evaporation of hydrometeors in precipitation from the anvil clouds of deep tropical convection. J. Atmos. Sci., 36, 669679.

    • Search Google Scholar
    • Export Citation
  • Penide, G., Kumar V. V. , Protat A. , and May P. T. , 2013: Statistics of drop size distribution parameters and rain rates for stratiform and convective precipitation during the north Australian wet season. Mon. Wea. Rev., 141, 3222–3237.

    • Search Google Scholar
    • Export Citation
  • Steiner, M., Houze R. A. Jr., and Yuter S. E. , 1995: Climatological characterization of three-dimensional storm structure from radar and rain gauge data. J. Appl. Meteor., 34, 19782007.

    • Search Google Scholar
    • Export Citation
  • Tan, J., Goddard J. W. F. , and Thurai M. , 1995: Applications of differential propagation phase in polarisation-diversity radars at S-band and C-band. Ninth International Conference on Antennas and Propagation, Vol. 2, Conf. Publ. 407, IEEE, 336341.

  • Testud, J., Le Bouar E. , Obligis E. , and Ali-Mehenni M. , 2000: The rain profiling algorithm applied to polarimetric weather radar. J. Atmos. Oceanic Technol., 17, 322356.

    • Search Google Scholar
    • Export Citation
  • Testud, J., Oury S. , Amayenc P. , and Black R. A. , 2001: The concept of ‘‘normalized'' distributions to describe raindrop spectra: A tool for cloud physics and cloud remote sensing. J. Appl. Meteor., 40, 11181140.

    • Search Google Scholar
    • Export Citation
  • Thurai, M., Bringi V. N. , and May P. T. , 2010: CPOL radar-derived drop size distribution statistics of stratiform and convective rain for two regimes in Darwin, Australia. J. Atmos. Oceanic Technol., 27, 932942.

    • Search Google Scholar
    • Export Citation
  • Tokay, A., and Short D. A. , 1996: Evidence from tropical raindrop spectra of the origin of rain from stratiform versus convective clouds. J. Appl. Meteor., 35, 355371.

    • Search Google Scholar
    • Export Citation
  • Ulbrich, C. W., and Atlas D. , 2002: On the separation of tropical convective and stratiform rains. J. Appl. Meteor. Climatol., 41, 188195.

    • Search Google Scholar
    • Export Citation
  • Ulbrich, C. W., and Atlas D. , 2007: Microphysics of raindrop size spectra: Tropical continental and maritime storms. J. Appl. Meteor. Climatol., 46, 17771791.

    • Search Google Scholar
    • Export Citation
  • Williams, C. R., Ecklund W. L. , and Gage K. S. , 1995: Classification of precipitating clouds in tropics using 915-MHz wind profilers. J. Atmos. Oceanic Technol., 12, 9961012.

    • Search Google Scholar
    • Export Citation
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