• Andersson, T., Alberoni P. P. , Mezzasalma P. , Michelson D. B. , and Nanni S. , 1997: Anomalous propagation: Identification from terrain and sea waves using vertical reflectivity profile analysis. Preprints, 28th Conf. on Radar Meteorology, Austin, TX, Amer. Meteor. Soc., 93–94.

  • Aoyagi, J., 1983: A study on the MTI weather radar system for rejecting ground clutter. Pap. Meteor. Geophys., 33 , 187243.

  • Battan, L. J., 1973: Radar Observation of the Atmosphere. University of Chicago Press, 324 pp.

  • Bech, J., Codina B. , Lorente J. , and Bebbington D. , 2002: Monthly and daily variations of radar anomalous propagation conditions: How “normal” is normal propagation? Preprints, Second European Conf. on Radar Meteorology, Delft, Netherlands, Copernicus GmbH–European Meteorological Society, 35–39.

  • Bellon, A., and Kilambi A. , 1999: Updates to the McGill RAPID (Radar Data Analysis, Processing and Interactive Display) system. Preprints, 29th Int. Conf. on Radar Meteorology, Montreal, QC, Canada, Amer. Meteor. Soc., 121–124.

  • Bellon, A., Fabry F. , and Austin G. L. , 1991: Errors due to space/time sampling strategies in high resolution radar data used in hydrology. Preprints, 25th Int. Conf. on Radar Meteorology, Paris, France, Amer. Meteor. Soc., 840–843.

  • Berenguer, M., Sempere-Torres D. , Sánchez-Diezma R. , and Pascual R. , 2005: Identification of clutter echoes using a fuzzy logic technique. Preprints, 32d Conf. on Radar Meteorology, Albuquerque, NM, Amer. Meteor. Soc., CD-ROM, P4R.1.

  • Corral, C., Sempere-Torres D. , Velasco C. , Sánchez-Diezma R. , Berenguer M. , Velasco E. , and Pastor J. , 2004: EHIMI: Herramienta de previsión hidrometeorológica integrada. Experiencia y resultados de la primera fase de implementación en Catalunya (in Spanish). Preprints, Jornadas sobre los Sistemas de Ayuda a la Decisión ante Problemas Hidráulicos e Hidrológicos en Tiempo Real, Madrid, Spain, CEDEX, 279–287.

  • da Silveira, R. B., and Holt A. R. , 2001: An automatic identification of clutter and anomalous propagation in polarization-diversity weather radar data using neural networks. IEEE Trans. Geosci. Remote Sens., 39 , 17771788.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Delrieu, G., and Creutin J. D. , 1995: Simulation of radar mountain returns using a digitized terrain model. J. Atmos. Oceanic Technol., 12 , 10381049.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Doviak, R. J., and Zrnic D. S. , 1992: Doppler Radar and Weather Observations. 2d ed. Academic Press, 562 pp.

  • Fabry, F., Frush C. , Zawadzki I. , and Kilambi A. , 1997: On the extraction of near-surface index of refraction using radar phase measurements from ground targets. J. Atmos. Oceanic Technol., 14 , 978987.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fiore, J. V., Farnsworth R. K. , and Huffman G. , 1986: Quality control of radar-rainfall data with VISSR satellite data. Preprints, 23d Conf. on Radar Meteorology and Conf. on Cloud Physics, Snowmass, CO, Amer. Meteor. Soc., JP15–JP18.

  • Franco, M., Sempere-Torres D. , Sánchez-Diezma R. , and Andrieu H. , 2004: Improvements in weather radar rain rate estimates at the ground using a methodology to identify the vertical profile of reflectivity from volume radar scans. Preprints, Third European Conf. on Radar Meteorology and Hydrology, Visby, Sweden, Copernicus GmbH–European Meteorological Society, 368–373.

  • Fulton, R. A., Breidenbach J. P. , Seo D-J. , Miller D. A. , and O’Bannon T. D. , 1998: The WSR-88D rainfall algorithm. Wea. Forecasting, 13 , 377395.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Giuli, D., Gherardelli M. , Freni A. , Seliga T. A. , and Aydin K. , 1991: Rainfall and clutter discrimination by means of dual-linear polarization radar measurements. J. Atmos. Oceanic Technol., 8 , 777789.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Grecu, M., and Krajewski W. E. , 2000: An efficient methodology for detection of anomalous propagation echoes in radar reflectivity data using neural networks. J. Atmos. Oceanic Technol., 17 , 121129.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hannesen, R., 2001: Quantitative precipitation estimation from radar data—A review of current methodologies. MUSIC European Commission Project, Deliverable 4.1, 31 pp.

  • Joss, J., and Waldvogel A. , 1990: Precipitation measurements and hydrology. Radar in Meteorology: Battan Memorial and 40th Anniversary of the Radar Meteorology Conference, D. Atlas, Ed., Amer. Meteor. Soc., 577–606.

    • Search Google Scholar
    • Export Citation
  • Joss, J., and Lee R. , 1995: The application of radar-gauge comparisons to operational precipitation profiles corrections. J. Appl. Meteor., 34 , 26122630.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Keeler, R. J., and Passarelli R. , 1990: Signal processing for atmospheric radars. Radar in Meteorology: Battan Memorial and 40th Anniversary of the Radar Meteorology Conference, D. Atlas, Ed., Amer. Meteor. Soc., 199–229.

    • Search Google Scholar
    • Export Citation
  • Kessinger, C., Ellis S. , and Van Andel J. , 2001: NEXRAD data quality: The AP clutter mitigation scheme. Preprints, 30th Int. Conf. on Radar Meteorology, Munich, Germany, Amer. Meteor. Soc., 707–709.

  • Kessinger, C., Ellis S. , and Van Andel J. , 2003: The radar echo classifier: A fuzzy logic algorithm for the WSR-88D. Preprints, Third Conf. on Artificial Intelligence Applications to the Environmental Science, Long Beach, CA, Amer. Meteor. Soc., 1–11.

  • Koistinen, J., 1991: Operational correction of radar rainfall errors due to the vertical profile of reflectivity. Preprints, 25th Int. Conf. on Radar Meteorology, Paris, France, Amer. Meteor. Soc., 91–96.

  • Kosko, B., 1992: Neural Networks and Fuzzy Systems: A Dynamical Systems Approach to Machine Intelligence. Prentice Hall, 449 pp.

  • Krajewski, W. F., and Vignal B. , 2001: Evaluation of anomalous propagation echo detection in WSR-88D data: A large sample case study. J. Atmos. Oceanic Technol., 18 , 807814.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kulie, M. S., Robinson M. , Marks D. A. , Ferrier B. S. , Rosenfeld D. , and Wolff D. B. , 1999: Operational processing of ground validation data for the Tropical Rainfall Measuring Mission. Preprints, 29th Int. Conf. on Radar Meteorology, Montreal, QC, Canada, Amer. Meteor. Soc., 736–739.

  • Lee, G. W., Cho Y-H. , Kim K-E. , and Zawadzki I. , 2005: Identification and removal of non-precipitation echoes using the characteristics of radar echoes. Preprints, 32d Conf. on Radar Meteorology, Albuquerque, NM, Amer. Meteor. Soc., CD-ROM, 4R.3.

  • Lee, R., Della Bruna G. , and Joss J. , 1995: Intensity of ground clutter and of echoes of anomalous propagation and its elimination. Preprints, 27th Conf. on Radar Meteorology, Vail, CO, Amer. Meteor. Soc., 651–652.

  • Martín, F., and de Esteban L. , 1994: Manual de interpretación radar (in Spanish). Instituto Nacional de Meteorología, 97 pp.

  • Meischner, P., Collier C. G. , Illingworth A. , Joss J. , and Randeu W. , 1997: Advanced weather radar systems in Europe: The COST 75 Action. Bull. Amer. Meteor. Soc., 78 , 14111430.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mendel, J. M., 1995: Fuzzy logic systems for engineering: A tutorial. Proc. IEEE, 83 , 345377.

  • Michelson, D. B., and Andersson T. , 1995: Identification and suppression of anomalous propagation echoes in two-dimensional radar images. Preprints, 27th Conf. on Radar Meteorology, Vail, CO, Amer. Meteor. Soc., 656–658.

  • Moszkowicz, S., Ciach G. J. , and Krajewski W. F. , 1994: Statistical detection of anomalous propagation in radar reflectivity patterns. J. Atmos. Oceanic Technol., 11 , 10261034.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Nicol, J. C., Tabary P. , Sugier J. , Parent-du-Chatelet J. , and Delrieu G. , 2003: Non-weather echo identification for conventional operational radar. Preprints, 31st Conf. on Radar Meteorology, Seattle, WA, Amer. Meteor. Soc., 542–545.

  • Pamment, J. A., and Conway B. J. , 1998: Objective identification of echoes due to anomalous propagation in weather radar data. J. Atmos. Oceanic Technol., 15 , 98113.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pascual, R., Callado R. , and Berenguer M. , 2004: Convective storm initiation in central Catalonia. Preprints, Third European Conf. on Radar Meteorology and Hydrology, Visby, Sweden, Copernicus GmbH–European Meteorological Society, 464–468.

  • Pratte, F., Gagnon R. , and Cornelious R. , 1993: Ground clutter characteristics and residue mapping. Preprints, 26th Conf. on Radar Meteorology, Norman, OK, Amer. Meteor. Soc., 50–52.

  • Pratte, F., Keeler R. J. , Gagnon R. , and Sirmans D. , 1995: Clutter processing during anomalous propagation conditions. Preprints, 27th Conf. on Radar Meteorology, Vail, CO, Amer. Meteor. Soc., 139–141.

  • Pratte, F., Ecoff D. , VanAndel J. , and Jeffrey Keeler R. , 1997: AP clutter mitigation in the WSR-88D. Preprints, 28th Conf. on Radar Meteorology, Austin, TX, Amer. Meteor. Soc., 504–507.

  • Rosenfeld, D., Amital E. , and Wolff D. B. , 1995: Classification of rain regimes by the three dimensional properties of reflectivity fields. J. Appl. Meteor., 34 , 198211.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ryzhkov, A. V., and Zrnic D. S. , 1998: Polarimetric rainfall estimation in the presence of anomalous propagation. J. Atmos. Oceanic Technol., 15 , 13201330.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sánchez-Diezma, R., Sempere-Torres D. , Delrieu G. , and Zawadzki I. , 2001: An Improved methodology for ground clutter substitution based on a pre-classification of precipitation types. Preprints, 30th Int. Conf. on Radar Meteorology, Munich, Germany, Amer. Meteor. Soc., 271–273.

  • Sempere-Torres, D., Porrà J. M. , and Creutin J. D. , 1997: Characterization of rainfall properties using the Drop Size Distribution: Application to autumn storms in Barcelona. Preprints, WMO-INM Int. Conf. on Cyclones and Hazardous Weather in the Mediterranean Area, Palma de Mallorca, Spain, Instituto Nacional de Meteorología, 621–628.

  • Sempere-Torres, D., Porrà J. M. , and Creutin J. D. , 1998: Experimental evidence of a general description for raindrop size distribution properties. J. Geophys. Res., 103 , 17851797.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sempere-Torres, D., Sánchez-Diezma R. , Berenguer M. , Pascual R. , and Zawadzki I. , 2003: Improving radar rainfall measurement stability using mountain returns in real time. Preprints, 31st Conf. on Radar Meteorology, Seattle, WA, Amer. Meteor. Soc., 220–221.

  • Smith, J. A., Baeck M. L. , Steiner M. , Bauer-Messmer B. , Zhao W. , and Tapia A. , 1996: Hydrometeorological assessments of the NEXRAD rainfall algorithms. NOAA National Weather Service Final Report, 59 pp.

  • Stanski, H. R., Wilson L. J. , and Burrows W. R. , 1989: Survey of common verification methods in meteorology. World Meteorological Organization World Weather Watch Tech. Rep. 8, 114 pp.

  • Steiner, M., and Smith J. A. , 2002: Use of three-dimensional reflectivity structure for automated detection and removal of non-precipitating echoes in radar data. J. Atmos. Oceanic Technol., 19 , 673686.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Steiner, M., Smith J. A. , Kessinger C. , and Ferrier B. S. , 1999: Evaluation of algorithm parameters for radar data quality control. Preprints, 29th Conf. on Radar Meteorology, Montreal, QC, Canada, Amer. Meteor. Soc., 582–585.

  • Vignal, B., Galli G. , Joss J. , and Germann U. , 2000: Three methods to determine profiles of reflectivity from volumetric radar data to correct precipitation estimates. J. Appl. Meteor., 39 , 17151726.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Weber, M. E., Stone M. L. , and Cullen J. A. , 1993: Anomalous propagation associated with thunderstorm outflows. Preprints, 26th Conf. on Radar Meteorology, Norman, OK, Amer. Meteor. Soc., 238–240.

  • Zawadzki, I., 1984: Factors affecting the precision of radar measurement of rain. Preprints, 22d Conf. on Radar Meteorology, Zurich, Switzerland, Amer. Meteor. Soc., 251–256.

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A Fuzzy Logic Technique for Identifying Nonprecipitating Echoes in Radar Scans

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  • 1 Grup de Recerca Aplicada en Hidrometeorologia, Universitat Politècnica de Catalunya, Barcelona, Spain
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Abstract

Because echoes caused by nonmeteorological targets significantly affect radar scans, contaminated bins must be identified and eliminated before precipitation can be quantitatively estimated from radar measurements.

Under mean propagation conditions, clutter echoes (mainly caused by targets such as mountains or large buildings) can be found in almost fixed locations. However, in anomalous propagation conditions, new clutter echoes may appear (sometimes over the sea), and they may be difficult to distinguish from precipitation returns. Therefore, an automatic algorithm is needed to identify clutter on radar scans, especially for operational uses of radar information (such as real-time hydrology).

In this study, a new algorithm is presented based on fuzzy logic, using volumetric data. It uses some statistics to highlight clutter characteristics (namely, shallow vertical extent, high spatial variability, and low radial velocities) to output a value that quantifies the possibility of each bin being affected by clutter (in order to remove those in which this factor exceeds a certain threshold).

The performance of this algorithm was compared against that of simply removing mean clutter echoes. Satisfactory results were obtained from an exhaustive evaluation of this algorithm, especially in those cases in which anomalous propagation played an important role.

Corresponding author address: Dr. Marc Berenguer, Grup de Recerca Aplicada en Hidrometeorologia, Universitat Politècnica de Catalunya, Gran Capità, 2-4 (edifici Nexus), despatx 102, Barcelona E-08034, Spain. Email: berengue@grahi.upc.edu

Abstract

Because echoes caused by nonmeteorological targets significantly affect radar scans, contaminated bins must be identified and eliminated before precipitation can be quantitatively estimated from radar measurements.

Under mean propagation conditions, clutter echoes (mainly caused by targets such as mountains or large buildings) can be found in almost fixed locations. However, in anomalous propagation conditions, new clutter echoes may appear (sometimes over the sea), and they may be difficult to distinguish from precipitation returns. Therefore, an automatic algorithm is needed to identify clutter on radar scans, especially for operational uses of radar information (such as real-time hydrology).

In this study, a new algorithm is presented based on fuzzy logic, using volumetric data. It uses some statistics to highlight clutter characteristics (namely, shallow vertical extent, high spatial variability, and low radial velocities) to output a value that quantifies the possibility of each bin being affected by clutter (in order to remove those in which this factor exceeds a certain threshold).

The performance of this algorithm was compared against that of simply removing mean clutter echoes. Satisfactory results were obtained from an exhaustive evaluation of this algorithm, especially in those cases in which anomalous propagation played an important role.

Corresponding author address: Dr. Marc Berenguer, Grup de Recerca Aplicada en Hidrometeorologia, Universitat Politècnica de Catalunya, Gran Capità, 2-4 (edifici Nexus), despatx 102, Barcelona E-08034, Spain. Email: berengue@grahi.upc.edu

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