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A Statistical Method for Reducing Sidelobe Clutter for the Ku-Band Precipitation Radar on board the GPM Core Observatory

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  • 1 Earth Observation Research Center, Japan Aerospace Exploration Agency, Tsukuba, Japan
  • | 2 Applied Electromagnetic Research Institute, National Institute of Information and Communications Technology, Koganei, Japan
  • | 3 Chief Engineer Office, Japan Aerospace Exploration Agency, Tsukuba, Japan
  • | 4 Goddard Earth Sciences Technology and Research, Morgan State University, Baltimore, Maryland
  • | 5 NASA Goddard Space Flight Center, Greenbelt, Maryland
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Abstract

A statistical method to reduce the sidelobe clutter of the Ku-band precipitation radar (KuPR) of the Dual-Frequency Precipitation Radar (DPR) on board the Global Precipitation Measurement (GPM) Core Observatory is described and evaluated using DPR observations. The KuPR sidelobe clutter was much more severe than that of the Precipitation Radar on board the Tropical Rainfall Measuring Mission (TRMM), and it has caused the misidentification of precipitation. The statistical method to reduce sidelobe clutter was constructed by subtracting the estimated sidelobe power, based upon a multiple regression model with explanatory variables of the normalized radar cross section (NRCS) of surface, from the received power of the echo. The saturation of the NRCS at near-nadir angles, resulting from strong surface scattering, was considered in the calculation of the regression coefficients.

The method was implemented in the KuPR algorithm and applied to KuPR-observed data. It was found that the received power from sidelobe clutter over the ocean was largely reduced by using the developed method, although some of the received power from the sidelobe clutter still remained. From the statistical results of the evaluations, it was shown that the number of KuPR precipitation events in the clutter region, after the method was applied, was comparable to that in the clutter-free region. This confirms the reasonable performance of the method in removing sidelobe clutter. For further improving the effectiveness of the method, it is necessary to improve the consideration of the NRCS saturation, which will be explored in future work.

Denotes Open Access content.

Publisher’s Note: This article was revised on 15 May 2017 to include the designation that it belongs to the Precipitation Retrieval Algorithms for GPM special collection.

Corresponding author address: Takuji Kubota, Earth Observation Research Center, Japan Aerospace Exploration Agency, 2-1-1 Sengen, Tsukuba-city, Ibaraki 305-8505, Japan. E-mail: kubota@ieee.org

This article is included in the Precipitation Retrieval Algorithms for GPM special collection.

Abstract

A statistical method to reduce the sidelobe clutter of the Ku-band precipitation radar (KuPR) of the Dual-Frequency Precipitation Radar (DPR) on board the Global Precipitation Measurement (GPM) Core Observatory is described and evaluated using DPR observations. The KuPR sidelobe clutter was much more severe than that of the Precipitation Radar on board the Tropical Rainfall Measuring Mission (TRMM), and it has caused the misidentification of precipitation. The statistical method to reduce sidelobe clutter was constructed by subtracting the estimated sidelobe power, based upon a multiple regression model with explanatory variables of the normalized radar cross section (NRCS) of surface, from the received power of the echo. The saturation of the NRCS at near-nadir angles, resulting from strong surface scattering, was considered in the calculation of the regression coefficients.

The method was implemented in the KuPR algorithm and applied to KuPR-observed data. It was found that the received power from sidelobe clutter over the ocean was largely reduced by using the developed method, although some of the received power from the sidelobe clutter still remained. From the statistical results of the evaluations, it was shown that the number of KuPR precipitation events in the clutter region, after the method was applied, was comparable to that in the clutter-free region. This confirms the reasonable performance of the method in removing sidelobe clutter. For further improving the effectiveness of the method, it is necessary to improve the consideration of the NRCS saturation, which will be explored in future work.

Denotes Open Access content.

Publisher’s Note: This article was revised on 15 May 2017 to include the designation that it belongs to the Precipitation Retrieval Algorithms for GPM special collection.

Corresponding author address: Takuji Kubota, Earth Observation Research Center, Japan Aerospace Exploration Agency, 2-1-1 Sengen, Tsukuba-city, Ibaraki 305-8505, Japan. E-mail: kubota@ieee.org

This article is included in the Precipitation Retrieval Algorithms for GPM special collection.

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