Automated ZDR Calibration on EEC Dual-Pol Weather Radar System

The accurate calibration of differential reflectivity (ZDR) is essential for the quantitative precipitation estimation (QPE) with dual-pol weather radar data. Various techniques have been developed for the ZDR calibration. The engineering approach of system calibration measures the gain/loss difference between the signal paths of horizontally-polarized (H) and vertically-polarized (V) channels. Considering the effect of temperature variation on the system gain/loss, the calibration would be better done frequently. In this regard, the engineering approach may not be efficient. The radar-data-analysis-based methods become more popular. The measurements of ground clutter, light rain, dry aggregated snow, and Bragg scattering can be used for ZDR calibration. These methods generally benefit from the statistical consistency in dual-pol radar measurements of those targets. The crosspolar power technique also utilizes the property of radar reciprocity. It is noted that most of these methods are inconvenient for the frequent online calibration so that the ZDR bias due to temperature variation is hard to monitor and calibrate in real time.

According to the data quality needed for accurate radar QPE, the ZDR calibration usually requires an accuracy of 0.1 dB and needs to account for the effect of temperature variation. Moreover, the online calibration is highly desirable so that the calibration can be done frequently without out of operation. Among all the existing ZDR calibration methods, the birdbath approach has been widely accepted as a robust method for estimating ZDR bias. This method utilizes the property of light rain statistically having zero ZDR measurement with radar antenna vertically pointing. Based on the birdbath method, Enterprise Electronics Corporation (EEC) recently developed an automated ZDR calibration function in EEC radar systems. With this function turned on, the radar can monitor the ZDR bias automatically with a customized interval (from minutes to hours/days). The birdbath scan is automatically run based on the rain intensity. The light rain data with quality control are then processed in real-time for estimating the ZDR bias. The historical and statistical results of ZDR bias are further analyzed for determining the real-time calibration term. The whole process is completely automated and does not need any human interference.

The ZDR calibration function has been tested in EEC’s inhouse C-band radar, deployed in Enterprise, Alabama. The current study presents the results of testing. The results demonstrate not only the high quality of EEC inhouse radar, which has small effect of temperature variation, but also the robust performance of automated ZDR calibration.