The authors thank Alan Free of the Radar Operations Center and David Warde of the National Severe Storms Laboratory for providing the radar data used to validate the technique. We also thank Valery Melnikov and David Warde for providing comments that improved the manuscript. Funding was provided by NOAA/Office of Oceanic and Atmospheric Research under NOAA–University of Oklahoma Cooperative Agreement NA11OAR4320072, U.S. Department of Commerce.
Dixon, M., and Hubbert J. C. , 2012: The separation of noise and signal components in Doppler radar returns. Extended Abstract, Seventh European Conf. on Radar in Meteorology and Hydrology (ERAD 2012), Toulouse, France, Météo-France, 13B-1. [Available online at http://www.eol.ucar.edu/projects/dynamo/spol/references/Separation_Noise_Signal.Dixon.ext_abs2012.pdf.]
Doviak, R. J., and Zrnić D. S. , 1993: Doppler Radar and Weather Observations. 2nd ed. Academic Press, 562 pp.
Fabry, F., 2001: Using radars as radiometers: Promises and pitfalls. Preprints, 30th Int. Conf. on Radar Meteorology, Munich, Germany, Amer. Meteor. Soc., P5.1. [Available online at https://ams.confex.com/ams/30radar/techprogram/paper_21576.htm.]
Hildebrand, P. H., and Sekhon R. S. , 1974: Objective determination of the noise level in Doppler spectra. J. Appl. Meteor., 13, 808–811.
Ivić, I. R., and Torres S. M. , 2010: Online determination of noise level in weather radars. Proc. Sixth European Conf. on Radar in Meteorology and Hydrology (ERAD 2010), Sibiu, Romania, Meteo Romania, 7 pp. [Available online at http://www.erad2010.org/pdf/oral/monday/6_ERAD2010_0094.pdf.]
Ivić, I. R., and Torres S. M. , 2011: Online determination of noise level in weather radars. Preprints, 27th Conf. on Interactive Information Processing Systems, Seattle, WA, Amer. Meteor. Soc., 369. [Available online at https://ams.confex.com/ams/91Annual/webprogram/Paper180709.html.]
Ivić, I. R., Zrnić D. S. , and Yu T.-Y. , 2009: Use of coherency to improve signal detection in dual-polarization weather radars. J. Atmos. Oceanic Technol., 26, 2474–2487.
Melnikov, V. M., and Zrnić D. S. , 2004: Simultaneous transmission mode for the polarimetric WSR-88D: Statistical biases and standard deviations of polarimetric variables. NOAA/NSSL Rep., 84 pp. [Available online at https://www.nssl.noaa.gov/publications/wsr88d_reports/SHV_statistics.pdf.]
Melnikov, V. M., and Zrnić D. S. , 2007: Autocorrelation and cross-correlation estimators of polarimetric variables. J. Atmos. Oceanic Technol., 24, 1337–1350.
Siggia, A. D., and Passarelli R. E. , 2004: Gaussian model adaptive processing (GMAP) for improved ground clutter cancellation and moment calculation. Third European Conference on Radar in Meteorology and Hydrology (ERAD) together with the COST 717 Final Seminar, Copernicus GmbH, 67–73.
Urkowitz, H., and Nespor J. D. , 1992: Obtaining spectral moments by discrete Fourier transform with noise removal in radar meteorology. IGARSS ’92: International Geoscience and Remote Sensing Symposium; International Space Year, IEEE, 12–14.
U.S. Department of Commerce, 2006: Part C: WSR-88D products and algorithms. Federal Meteorological Handbook 11, Department of Commerce, FCM-H11C-2006. [Available online at http://www.ofcm.gov/fmh11/fmh11partc/pdf/FMH-11-PartC-April2006.pdf.]
A volume scan consists of the radar making multiple 360° scans of the atmosphere, where elevation angles are gradually increasing.
A radial is a set of data originating from M consecutive transmissions that is used to produce a ray of meteorological variables.
In the interest of briefness, radar resolution volume is referred to as volume in the remainder of the text.