Rainfall and Clutter Discrimination by Means of Dual-linear Polarization Radar Measurements

D. Giuli Dipartimento di ingegneria Elettronica, Firenze, Italy

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M. Gherardelli Dipartimento di ingegneria Elettronica, Firenze, Italy

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A. Freni Dipartimento di ingegneria Elettronica, Firenze, Italy

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T. A. Seliga Department of Electrical Engineering, University of Washington, Seattle, Washington

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K. Aydin Communications and Space Sciences Laboratory, Department of Electrical and Computer Engineering, Pennsylvania State University, University Park, Pennsylvania

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Abstract

The presence of undetected mixed-phase precipitation or superimposed intense clutter can cause serious errors in the estimation of rainfall rate and other parameters of precipitation occurring in the radar scattering volume. To reduce or avoid these errors it is necessary to distinguish between the rain echo, and that due to other types of precipitation, and between precipitation radar echoes and ground clutter. Multiparameter radar measurements may be exploited for this discrimination. In particular, it is demonstrated that dual-linear polarization measurements may play a major role in this process. Sample radar data are employed to illustrate several different tests to classify radar data: the results refer to comparisons of dual-polarized echoes due to precipitation (rain or mixed-phase event) and land with echoes from land alone. This is illustrated by example through the application of a series of tests on a clutter-contaminated dual-polarized dataset obtained during the May Polarization Experiments (MAYPOLE) 1984 field program in Colorado.

Abstract

The presence of undetected mixed-phase precipitation or superimposed intense clutter can cause serious errors in the estimation of rainfall rate and other parameters of precipitation occurring in the radar scattering volume. To reduce or avoid these errors it is necessary to distinguish between the rain echo, and that due to other types of precipitation, and between precipitation radar echoes and ground clutter. Multiparameter radar measurements may be exploited for this discrimination. In particular, it is demonstrated that dual-linear polarization measurements may play a major role in this process. Sample radar data are employed to illustrate several different tests to classify radar data: the results refer to comparisons of dual-polarized echoes due to precipitation (rain or mixed-phase event) and land with echoes from land alone. This is illustrated by example through the application of a series of tests on a clutter-contaminated dual-polarized dataset obtained during the May Polarization Experiments (MAYPOLE) 1984 field program in Colorado.

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