Articles | Volume 13, issue 2
Atmos. Meas. Tech., 13, 537–551, 2020
https://doi.org/10.5194/amt-13-537-2020
Atmos. Meas. Tech., 13, 537–551, 2020
https://doi.org/10.5194/amt-13-537-2020

Research article 07 Feb 2020

Research article | 07 Feb 2020

Improved fuzzy logic method to distinguish between meteorological and non-meteorological echoes using C-band polarimetric radar data

Shuai Zhang et al.

Related authors

Interpreting estimated observation error statistics of weather radar measurements using the ICON-LAM-KENDA system
Yuefei Zeng, Tijana Janjic, Yuxuan Feng, Ulrich Blahak, Alberto de Lozar, Elisabeth Bauernschubert, Klaus Stephan, and Jinzhong Min
Atmos. Meas. Tech., 14, 5735–5756, https://doi.org/10.5194/amt-14-5735-2021,https://doi.org/10.5194/amt-14-5735-2021, 2021
Short summary

Related subject area

Subject: Others (Wind, Precipitation, Temperature, etc.) | Technique: Remote Sensing | Topic: Data Processing and Information Retrieval
High-temporal-resolution wet delay gradients estimated from multi-GNSS and microwave radiometer observations
Tong Ning and Gunnar Elgered
Atmos. Meas. Tech., 14, 5593–5605, https://doi.org/10.5194/amt-14-5593-2021,https://doi.org/10.5194/amt-14-5593-2021, 2021
Short summary
Boundary layer water vapour statistics from high-spatial-resolution spaceborne imaging spectroscopy
Mark T. Richardson, David R. Thompson, Marcin J. Kurowski, and Matthew D. Lebsock
Atmos. Meas. Tech., 14, 5555–5576, https://doi.org/10.5194/amt-14-5555-2021,https://doi.org/10.5194/amt-14-5555-2021, 2021
Short summary
GNSS-based water vapor estimation and validation during the MOSAiC expedition
Benjamin Männel, Florian Zus, Galina Dick, Susanne Glaser, Maximilian Semmling, Kyriakos Balidakis, Jens Wickert, Marion Maturilli, Sandro Dahlke, and Harald Schuh
Atmos. Meas. Tech., 14, 5127–5138, https://doi.org/10.5194/amt-14-5127-2021,https://doi.org/10.5194/amt-14-5127-2021, 2021
Short summary
Meteor radar observations of polar mesospheric summer echoes over Svalbard
Joel P. Younger, Iain M. Reid, Chris L. Adami, Chris M. Hall, and Masaki Tsutsumi
Atmos. Meas. Tech., 14, 5015–5027, https://doi.org/10.5194/amt-14-5015-2021,https://doi.org/10.5194/amt-14-5015-2021, 2021
Short summary
Analysis of the microphysical properties of snowfall using scanning polarimetric and vertically pointing multi-frequency Doppler radars
Mariko Oue, Pavlos Kollias, Sergey Y. Matrosov, Alessandro Battaglia, and Alexander V. Ryzhkov
Atmos. Meas. Tech., 14, 4893–4913, https://doi.org/10.5194/amt-14-4893-2021,https://doi.org/10.5194/amt-14-4893-2021, 2021
Short summary

Cited articles

Bringi, V. N. and Chandrasekar, V.: Polarimetric Doppler Weather Radar, Cambridge University Press, Cambridge, UK, 2001. 
Cho, Y. H., Lee, G., Kim, K. E., and Zawadzki, I.: Identification and Removal of Ground Echoes and Anomalous Propagation Using the Characteristics of Radar Echoes, J. Atmos. Ocean. Tech., 23, 1206–1222, 2006. 
Crum, T. D. and Alberty, R. L.: The WSR-88D and the WSR-88D Operational Support Facility, B. Am. Meteorol. Soc., 74, 1669–1688, 1993. 
Doswell III, C. A., Davies-Jones, R., and Keller, D. L.: On summary measures of skill in rare event forecasting based on contingency tables, Weather Forecast., 5, 576–585, 1990. 
Doviak, R. J. and Zrnić, D. S.: Doppler radar and weather observations, Academic Press, Mineola, NY, 2nd edn., Dover Publications, Mineola, N.Y., 2006. 
Download
Short summary
The discrimination between meteorological and non-meteorological echoes is necessary to obtain better meteorological application performance. However, the widely used algorithms have high expectations for polarimetric data, which have similar characteristics between meteorological and non-meteorological echoes in the weak-signal regions. Therefore, an improved fuzzy logic method is proposed in this paper to improve the classification performance in weak-signal regions.