An Attempt to Estimate Differential Reflectivity Bias Using Volume Scan Dataset Obtained by C-Band Polarimetric Radar on Board R/V <i>Mirai</i>
Author:
Affiliation:
1. Japan Agency for Marine-Earth Science and Technology (JAMSTEC)
Publisher
Meteorological Society of Japan
Subject
Atmospheric Science
Link
https://www.jstage.jst.go.jp/article/sola/19/0/19_2023-030/_pdf
Reference21 articles.
1. Cunningham, J. G., W. D. Zittel, R. R. Lee, R. I. Ice, and N. P. Hoban, 2013: Methods for identifying systematic differential reflectivity (ZDR) biases on the operational WSR-88D network. Proc. 36th Conf. Radar Meteor., 9B.5 (Available online at: https://ams.confex.com/ams/36Radar/webprogram/Paper228792.html, accessed July 2023).
2. Dolan, B., S. A. Rutledge, S. Lim, V. Chandrasekar, and M. Thurai, 2013: A robust C-band hydrometeor identification algorithm and application to a long-term polarimetric radar dataset. J. Appl. Meteor. Climatol., 52, 2162-2186, doi:10.1175/JAMC-D-12-0275.1.
3. Geng, B., and M. Katsumata, 2016: Beam blockage identification for weather radars on board the R/V Mirai using archived data. JAMSTEC Rep. Res. Dev., 22, 1-12, doi:10.5918/jamstecr.22.1.
4. Geng, B., and M. Katsumata, 2020: An algorithm for detecting and removing the spurious differential phase observed by C-band polarimetric radar in the rain. J. Meteor. Soc. Japan, 98, 585-613, doi:10.2151/jmsj.2020-031.
5. Gorgucci, E., G. Scarchilli, and V. Chandrasekar, 1999: A procedure to calibrate multiparameter weather radar using properties of the rain medium. IEEE Trans. Geosci. Remote Sens., 37, 269-276, doi:10.1109/36.739161.
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