An Accurate Retrieval of Cloud Droplet Effective Radius for Single-Wavelength Cloud Radar

The cloud droplets effective radius is a key feature that plays a critical role in influencing cloud microphysical processes and radiative effects. Accurate quantification of cloud effective radius (CER) is essential for advancing our understanding of cloud microphysics, refining cloud parameterization, and improving future climate prediction. Nonetheless, the accuracy of current CER retrieval algorithms, particularly relying on millimeter-wavelength cloud radar, is often largely affected by assumptions about the cloud droplet number concentration, inappropriate empirical coefficients, attenuated radar reflectivity, and limitations of other auxiliary instruments. In this study, we developed a novel CER retrieval algorithm for single-wavelength radar by leveraging the interconnections between CER, liquid water content (LWC), and cloud radar reflectivity. Unlike the previous studies, we first derive the LWC from a self-consistent method based on cloud liquid water mass absorption instead of empirical relationships. Subsequently, we correct the radar measured reflectivity attenuated by cloud water and perform sensitivity analysis to select an optimal parameter that minimizes the uncertainty associated with the given cloud droplet size distribution (DSD) assumption. Then, the CER is calculated from the retrieved LWC, corrected reflectivity, and the optimal parameter. We compared the frequency distribution, vertical structure, and error fraction of the retrieved CER with aircraft in situ measurements. Our results demonstrate higher consistency with in situ data compared to traditional empirical algorithms. Furthermore, the cloud optical thickness (COT) derived from the CER shows a much better agreement with Moderate Resolution Imaging Spectroradiometer (MODIS) products, which provides additional validation for the efficacy of our method in investigating cloud microphysical properties.