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 D m using a dual-frequency cloud radar. Since the differential reflectivity Z dr is ineffective for D m retrieval at 94 GHz, and simulations demonstrate a strong dependence of the differential backscatter phase δ co on D m , the estimation of δ co takes precedence in this paper. Notably, δ co 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 δ co and its associated error is presented. Leveraging simulation results, confidence intervals for D m that align with δ co confidence intervals are retrieved. The assessment of D m and its confidence interval at 35 and 94 GHz is conducted employing disdrometer-derived D m . 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 D m below 1 mm, as the disdrometer-derived D m may exhibit an overestimation, while the cloud-radar-derived D m may exhibit an underestimation. The combination of 35 and 94 GHz serves to diminish the confidence interval associated with the retrieved D m .