Mitigating radome-induced bias in X-band weather radar polarimetric moments using an adaptive discrete Fourier transform algorithm

Abstract. In recent years, the application of compact and cost-effective deployable X-band polarimetric radars has gained in popularity, particularly in regions with complex terrain. The deployable radars generally use a radome constructed by joining multiple panels using metallic threads to facilitate easy transportation. As a part of the ESPOIRS project, Laboratoire de l'Atmosphère et des Cyclones has acquired an X-band meteorological radar with a four-panel radome configuration. In this study, we investigated the effect of the radome on the measured polarimetric variables, particularly differential reflectivity and differential phase. Our observations reveal that the metallic threads connecting the radome panels introduce power loss at vertical polarization, leading to a positive bias in the differential reflectivity values. To address the spatial variability bias observed in differential reflectivity and differential phase, we have developed a novel algorithm based on the discrete Fourier transform. The algorithm's performance was tested during an intense heavy-rainfall event caused by Cyclone Batsirai on Réunion Island. The comparative and joint histogram analysis demonstrates the algorithm's effectiveness in correcting the spatial bias in the polarimetric variables.

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Publication Details

Journal
Atmospheric measurement techniques
Published
2025-03-07
DOI
https://doi.org/10.5194/amt-18-1185-2025
Primary Topic
Precipitation Measurement and Analysis
Type
article
Field-Weighted Citation Impact
0.00

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article

Mitigating radome-induced bias in X-band weather radar polarimetric moments using an adaptive discrete Fourier transform algorithm

T. Padmanabhan, Guillaume Lesage, Ambinintsoa Volatiana Ramanamahefa, Joël Van Baelen
Atmospheric measurement techniques
Precipitation Measurement and Analysis
article

Mitigating radome-induced bias in X-band weather radar polarimetric moments using an adaptive discrete Fourier transform algorithm

T. Padmanabhan, Guillaume Lesage, Ambinintsoa Volatiana Ramanamahefa, Joël Van Baelen
article en

Abstract

Abstract. In recent years, the application of compact and cost-effective deployable X-band polarimetric radars has gained in popularity, particularly in regions with complex terrain. The deployable radars generally use a radome constructed by joining multiple panels using metallic threads to facilitate easy transportation. As a part of the ESPOIRS project, Laboratoire de l'Atmosphère et des Cyclones has acquired an X-band meteorological radar with a four-panel radome configuration. In this study, we investigated the effect of the radome on the measured polarimetric variables, particularly differential reflectivity and differential phase. Our observations reveal that the metallic threads connecting the radome panels introduce power loss at vertical polarization, leading to a positive bias in the differential reflectivity values. To address the spatial variability bias observed in differential reflectivity and differential phase, we have developed a novel algorithm based on the discrete Fourier transform. The algorithm's performance was tested during an intense heavy-rainfall event caused by Cyclone Batsirai on Réunion Island. The comparative and joint histogram analysis demonstrates the algorithm's effectiveness in correcting the spatial bias in the polarimetric variables.

Atmospheric measurement techniquesVol. 18(5)
Centre National de la Recherche Scientifique (FR), Laboratoire de l'Atmosphère et des Cyclones (RE), University of Oklahoma (US)
European Commission, Secrétariat Général pour les Affaires Régionales, Etat en Région Aquitaine, Centre National de la Recherche Scientifique, Interreg
Openalex Percentile: Top 96%
Precipitation Measurement and Analysis
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Mitigating radome-induced bias in X-band weather radar polarimetric moments using an adaptive discrete Fourier transform algorithm — T. Padmanabhan, Guillaume Lesage, et al. · Atmospheric measurement techniques (2025) | TGRS Research Map | TGRS