Abstract: Reflectivity calibration errors, attenuation in regions prone to rainfall, and water cover over cloud radar antennas have severely impacted the microphysical and dynamic parameters retrieved using reflectivity spectral density data; examining the errors involved with retrieving microphysical and dynamic parameters is a crucial problem that needs resolution. This paper presents a retrieval algorithm for vertical air motion (V_air) and raindrop size distribution (DSD) based on reflectivity spectral density data and dual-wavelength ratio (DWR) constraints with a Ka/Ku dual-wavelength cloud radar (DWCR), which aims to reduce the effects of observation bias introduced by calibration and attenuation of water cover over cloud radar antenna on reflectivity. The disdrometer data were employed to analyze the retrieved parameters. Furthermore, the effects of vertical air speed on retrieved microphysical parameters are discussed. In the algorithm (DWR-SZ), V_air retrieved from a single Ka/Ku band CR (ST) and DWCR algorithms (DWSZ) are merged to form V_air in all observation areas, following which the initial DSD and attenuation are retrieved using the DWSZ algorithm. Finally, DWR between the first and last ranges in the liquid area in a beam is utilized to adjust the reflectivity bias and the retrieved final DSD to minimize the difference between the observed cloud radar and the calculated DWR. Two convective precipitation cases on June 8, 2020, and June 1, 2021, in Longmen, Guangdong Province, were used to examine the retrieved results. The results demonstrate that the radar sensitivity variations have little effect on V_air obtained from the DWSZ; however, the DWSZ cloud is only employed in the areas containing large raindrops (diameter > 1.8 mm). ST algorithms with Ka and Ku data underestimated V_air; however, the V_airr is reasonable at low altitudess with reflectivity weaker than 35 dBZ. A highly sensitive work mode with pulse compressions could enhance the V_air retrieval bias. Merged V_air from the ST and DWSZ algorithms is reasonable. The attenuation and far radar range could introduce the underestimation of V_air with ST algorithms. Moreover, the underestimations of V_air in the solid precipitation area are negotiable due to the sharp variation and narrow reflectivity spectral density data. Furthermore, employing the constraint conditions of DWR reduced the bias of observed reflectivity and the effects of water cover over the antenna, thereby improving the retrieval results. V_air from the ST used in DWR-SZ overestimated the drop number, liquid water content (LWC), and attenuation coefficient and underestimated the drop size; however, it has no effect on the reflectivity bias produced by water cover over the antenna.