Applicability of self-consistency calibration method for polarimetric cloud radars

Cloud radars are powerful tools for investigating cloud formation, radiative processes, and cloud microphysics. In recent years, polarimetric cloud radars have become increasingly common around the world. Since many cloud property retrieval techniques rely on accurately measured reflectivity, ensuring high-quality calibration is essential. The most widely used calibration approach is one based on disdrometer measurements, but this method carries significant uncertainties, particularly due to the vertical variability of rainfall characteristics. Another conventional method is the one based on point target observations, i.e. using hard targets such as corner and sphere reflectors (Toledo et al.,2020), but it is work intensive and difficult to carry out. Another method is the calibration transfer of a radar to those that are not calibrated yet (Jorquera et al.,2023) for e.g. BASTA radar in CCRES. The main disadvantage of the calibration transfer method is the high time consumption. Since the time needed to ship the reference radar to each location and carrying out the calibration is high, in a year maximum 2 or 3 radars can be calibrated. Another method of calibration is by comparison of observations by ground-based cloud radars and space-borne W-band radars in CloudSat and EarthCARE. EarthCARE (CloudSat) flight cycle of 25 (16) days and the requirement in pure ice nonprecipitating clouds during an overpass, makes this method mainly applicable for long-term calibration monitoring. To address all these limitations and complement in cloud radar calibration methods, A. Myagkov et al. (2020) introduced a self-consistency calibration technique that makes use of the polarization capabilities of W-band cloud radars. In this study, we assess the suitability of the self-consistency calibration method and identify the modifications required to make the approach more user-friendly and practical for operation.For this study, we have used 94 GHz cloud radar data operated at 300 elevation angle during days having rainfall rate less than 20 mm/hr. The methodology of self-consistency method consists of 4 steps. 1) Using Rayleigh Plateau detection method (Unal and van den Brule,2024), retrieve propagational (Kdp) and backscattering (δ) components from differential phase (φ) and, differential attenuation (Adp). 2) Calculate non-attenuated reflectivity Z0. 3) Calculate Kdp and Adp using Z0, δ and the coefficients given in A. Myagkov et al. (2020). 4) Compare the measured and calculated Kdp and Adp, and find the best fit for calibration coefficient.The major findings of this study are summarized as follows:1) A 30° elevation angle and rainfall rate below 20 mm/hr are not the only criteria required for applying the self-consistency method. The values of differential backscatter phase(δ) and Doppler spectrum width also play important roles. 2) The influence of surface temperature on the method has been examined.3)The criteria for selecting suitable cloud radar observations for the self-consistency calibration approach have been clearly identified.4)In addition to the calibration of reflectivity, the retrieval of the one-way attenuation profile is shown to be another significant output of the self-consistency calibration technique.