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

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.

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“…A calibration transfer standard is facilitated by the highly stable instruments and careful attention to instrument design for the GPM‐CO. With regards to the DPR, a diagnosed side‐lobe clutter issue was corrected (Kubota et al ., ), and overall performance demonstrated in Kubota et al . (), Toyoshima et al .…”

Similarities and Improvements of GPM Dual-Frequency Precipitation Radar (DPR) upon TRMM Precipitation Radar (PR) in Global Precipitation Rate Estimation, Type Classification and Vertical Profiling

“…For TRMM PR, previous studies have pointed out that because of angle dependency in the outer swath, the near-nadir (NN) statistics are assumed to be of the highest quality in terms of observation limitation [53]. Kubota et al [54] found that the sidelobe clutter in KuPR in DPR is stronger than that in TRMM PR, and thus, it cannot be ignored. Therefore, we then selected the matchup pixels of DPR MS swath and TRMM PR inner swath (the central 25 beams) within the same time and space interval as Group 1.…”

GPM Satellite Radar Measurements of Precipitation and Freezing Level in Atmospheric Rivers: Comparison With Ground‐Based Radars and Reanalyses

“…The along‐track horizontal footprint of the Ka and Ku band matched scan swath is ~125 km (25 horizontal bins in the along‐track direction). Only data from the five cross‐track bins closest to the nadir‐pointing ray at the center of the swath were used on account of increasing surface clutter with increasing distance from nadir (Kubota et al, ), and in order to avoid sampling precipitation features at an angle, which bias both precipitation and bright‐band retrievals (Hamada & Takaybu, ; Hirose et al, ). GPM completes roughly 16 orbits per day between 65°N and 65°S, and the 2ADPR product has a latency of less than 24 h. The study period spanned three winter seasons (October through March; 2014–2017), focusing on the period of the year during which ARs routinely make landfall in California.…”