Evaluation of the Self-Consistency Principle for Calibration of the CASA Radar Network Using Properties of the Observed Precipitation Medium

A network of four weather radars was deployed as part of the Center for Collaborative and Adaptive Sensing of the Atmosphere (CASA). The radars operate at the X-band frequency and are capable of polarimetric measurements. The rainfall polarimetric self-consistency principle for absolute calibration is evaluated and applied to the CASA radars´ data to estimate any bias in the reflectivity (Z) measurements. Moreover, prior to the application of the self-consistency principle, bias error correction of differential reflectivity (Z_DR) measurements is required. Two different approaches were evaluated for Z_DR bias correction, the dry aggregated snow approach and the light rain approach. Results of Z_DR calibration show an accuracy of 0.2 dB or better in bias estimation for the two events analyzed when both methods are compared. Moreover, results show a calibration accuracy of 0.6 dB or better for the Z bias estimated using the self-consistency principle. For verification of results, Z bias estimates from the self-consistency principle are compared with Z bias estimated from the comparison between the CASA X-band and the two nearby WSR-88D S-band radars´ data. Comparison of the two approaches shows a difference in the Z bias estimation of 0.61 dB or better, which validates the use of the self-consistency principle in rainfall for the absolute radar calibration of the CASA radars. Results show that the self-consistency principle provides a means to estimate bias errors in the radar power measurements from a specific observed medium with a set of space-time characteristics that are not taken into account in the radar hardware relative calibration.