Exploring Millimeter-Wavelength Radar Capabilities for Raindrop Size Distribution Retrieval: Estimating Mass-Weighted Mean Diameter from the Differential Backscatter Phase.

Accurate precipitation characterization relies on the estimation of raindrop size distribution (RDSD) from observations. While various techniques using centimeter-wavelength radars have been proposed for RDSD retrieval, the potential of millimeter-wavelength polarimetric radars, offering enhanced spatial and temporal resolution while capturing light to moderate rain, remains unexplored. This study focuses on retrieving the mass-weighted mean diameter Dm using a dual-frequency cloud radar. Since the differential reflectivity Zdr is ineffective for Dm retrieval at 94 GHz, and simulations demonstrate a strong dependence of the differential backscatter phase δco on Dm, the estimation of δco takes precedence in this paper. Notably, δco remains unaffected by attenuation and polarimetric calibration. Addressing the initial requirement of disentangling backscattering and propagation effects at millimeter wavelength, an automatic algorithm is proposed to detect Rayleigh plateaus in the spectral domain. Subsequently, a methodology for estimating δco and its associated error is presented. Leveraging simulation results, confidence intervals for Dm that align with δco confidence intervals are retrieved. The assessment of Dm and its confidence interval at 35 and 94 GHz is conducted employing disdrometer-derived Dm. The results demonstrate a comprehensive concordance within a margin of 0.2 mm, underscoring the cloud radar's efficacy in delineating nuanced variations in the raindrop mean diameter versus altitude. The validation process encounters difficulties for Dm below 1 mm, as the disdrometer-derived Dm may exhibit an overestimation, while the cloud-radar-derived Dm may exhibit an underestimation. The combination of 35 and 94 GHz serves to diminish the confidence interval associated with the retrieved Dm. [ABSTRACT FROM AUTHOR]