Radar and Remote Sensing

Making Use of Simulated Time-series Dual-polarization
Radar Data to Quantify the Performance of
Several Rain Attenuation Correction Algorithms

Ryan May
ARRC / SoM

27 February 2014, 1:15 PM

National Weather Center, Room 1313
120 David L. Boren Blvd.
University of Oklahoma
Norman, OK

Correction for rain attenuation is an important data quality issue when using data collected by radars operating at attenuating wavelengths, specifically C and X bands. Such issues are especially important for quantitative use of the data, like rainfall estimation, where a 3dB error in reflectivity factor can result in more than 60% error in the rainfall estimate. In this work, we make use of simulated time-series dual- polarization radar data to quantify the performance of several rain attenuation correction algorithms: linear phidp, ZPHI, self-consistent, and fully self-consistent. Using the simulated data and respective truth fields, we examine the algorithms' performance in detail, across a variety of scattering and microphysics configurations.

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