Articles | Volume 8, issue 10
https://doi.org/10.5194/amt-8-3985-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/amt-8-3985-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
01 Oct 2015
Research article |
| 01 Oct 2015
Fuzzy logic filtering of radar reflectivity to remove non-meteorological echoes using dual polarization radar moments
D. R. L. Dufton
CORRESPONDING AUTHOR
Institute for Climate and Atmospheric Science, University of Leeds, Leeds, UK
National Centre for Atmospheric Science, University of Leeds, Leeds, UK
C. G. Collier
Institute for Climate and Atmospheric Science, University of Leeds, Leeds, UK
National Centre for Atmospheric Science, University of Leeds, Leeds, UK
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Cited
14 citations as recorded by crossref.
- Offshore wind turbine clutter characteristics and identification in operational C‐band weather radar measurements W. Hall et al. https://doi.org/10.1002/qj.2959
- Investigation of Weather Radar Quantitative Precipitation Estimation Methodologies in Complex Orography M. Montopoli et al. https://doi.org/10.3390/atmos8020034
- Radar-Derived Structural and Precipitation Characteristics of ZDR Columns within Warm-Season Convection over the United Kingdom D. Plummer et al. https://doi.org/10.1175/JAMC-D-17-0134.1
- The NCAS mobile dual-polarisation Doppler X-band weather radar (NXPol) R. Neely III et al. https://doi.org/10.5194/amt-11-6481-2018
- Full-Year Evaluation of Nonmeteorological Echo Removal with Dual-Polarization Fuzzy Logic for Two C-Band Radars in a Temperate Climate A. Overeem et al. https://doi.org/10.1175/JTECH-D-19-0149.1
- Adopting a Neuro-Fuzzy Logic Method for Fall Armyworm Detection and Monitoring Using C-Band Polarimetric Doppler Weather Radar With Field Verification F. Maniraguha et al. https://doi.org/10.1109/TGRS.2024.3395281
- Clutter Elimination Algorithm for Non-Precipitation Echo of Radar Data Considering Meteorological and Observational Properties in Polarimetric Measurements Y. Oh et al. https://doi.org/10.3390/rs12223790
- Wasserstein Generative Adversarial Networks Based Data Augmentation for Radar Data Analysis H. Lee et al. https://doi.org/10.3390/app10041449
- Correcting for Mobile X-Band Weather Radar Tilt Using Solar Interference D. Dufton et al. https://doi.org/10.3390/rs15245637
- Enhancing the accuracy of weather radar heavy rainfall estimates in mountainous regions using combined radar quality indices M. Methaprayun et al. https://doi.org/10.1016/j.jhydrol.2025.133907
- Improving weather radar precipitation maps: A fuzzy logic approach M. Silver et al. https://doi.org/10.1016/j.atmosres.2019.104710
- A simple biota removal algorithm for 35 GHz cloud radar measurements M. Kalapureddy et al. https://doi.org/10.5194/amt-11-1417-2018
- Assessing precipitation from a dual-polarisation X-band radar campaign using the Grid-to-Grid hydrological model J. Wallbank et al. https://doi.org/10.1016/j.jhydrol.2022.128311
- Clear-Air Echoes Observed by Ka-band Polarimetric Cloud Radar: A Case Study on Insect Echoes in the Tokyo Metropolitan Area, Japan T. OHIGASHI et al. https://doi.org/10.2151/jmsj.2021-006
14 citations as recorded by crossref.
- Offshore wind turbine clutter characteristics and identification in operational C‐band weather radar measurements W. Hall et al. https://doi.org/10.1002/qj.2959
- Investigation of Weather Radar Quantitative Precipitation Estimation Methodologies in Complex Orography M. Montopoli et al. https://doi.org/10.3390/atmos8020034
- Radar-Derived Structural and Precipitation Characteristics of ZDR Columns within Warm-Season Convection over the United Kingdom D. Plummer et al. https://doi.org/10.1175/JAMC-D-17-0134.1
- The NCAS mobile dual-polarisation Doppler X-band weather radar (NXPol) R. Neely III et al. https://doi.org/10.5194/amt-11-6481-2018
- Full-Year Evaluation of Nonmeteorological Echo Removal with Dual-Polarization Fuzzy Logic for Two C-Band Radars in a Temperate Climate A. Overeem et al. https://doi.org/10.1175/JTECH-D-19-0149.1
- Adopting a Neuro-Fuzzy Logic Method for Fall Armyworm Detection and Monitoring Using C-Band Polarimetric Doppler Weather Radar With Field Verification F. Maniraguha et al. https://doi.org/10.1109/TGRS.2024.3395281
- Clutter Elimination Algorithm for Non-Precipitation Echo of Radar Data Considering Meteorological and Observational Properties in Polarimetric Measurements Y. Oh et al. https://doi.org/10.3390/rs12223790
- Wasserstein Generative Adversarial Networks Based Data Augmentation for Radar Data Analysis H. Lee et al. https://doi.org/10.3390/app10041449
- Correcting for Mobile X-Band Weather Radar Tilt Using Solar Interference D. Dufton et al. https://doi.org/10.3390/rs15245637
- Enhancing the accuracy of weather radar heavy rainfall estimates in mountainous regions using combined radar quality indices M. Methaprayun et al. https://doi.org/10.1016/j.jhydrol.2025.133907
- Improving weather radar precipitation maps: A fuzzy logic approach M. Silver et al. https://doi.org/10.1016/j.atmosres.2019.104710
- A simple biota removal algorithm for 35 GHz cloud radar measurements M. Kalapureddy et al. https://doi.org/10.5194/amt-11-1417-2018
- Assessing precipitation from a dual-polarisation X-band radar campaign using the Grid-to-Grid hydrological model J. Wallbank et al. https://doi.org/10.1016/j.jhydrol.2022.128311
- Clear-Air Echoes Observed by Ka-band Polarimetric Cloud Radar: A Case Study on Insect Echoes in the Tokyo Metropolitan Area, Japan T. OHIGASHI et al. https://doi.org/10.2151/jmsj.2021-006
Saved (final revised paper)
Latest update: 16 Jun 2026
Short summary
This paper describes a radar echo classification scheme, used to identify and remove non-meteorlogical echoes from X-band radar data. The classifier uses fuzzy logic to incorporate multiple radar moments, including linear texture fields, into the decision scheme. The scheme is trained on a limited subset of data from a short field deployment. The feasibility of the scheme is then demonstrated with a range of examples from two field deployments in the UK.
This paper describes a radar echo classification scheme, used to identify and remove...
