Understanding the microphysical properties of ice hydrometeors remains challenging. This study develops and evaluates a cloud-ice retrieval algorithm that synergistically uses W-band radar, Ku/Ka-band radar, and millimeter-wave radiometer observations. This strategy enables to observe deep inside precipitating clouds unreachable by conventional combined radar–lidar measurements due to severe attenuation.</p> <p>The retrieved cloud microphysical parameters are compared with aircraft in situ measurements from the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) campaign. The bias between retrieved values and in situ measurements varied by roughly two orders of magnitude depending on the particle habit assumptions. A mixture of rosette and snowflake habits based on physical considerations yielded the best overall performance. Under this habit assumption, the mean ratios of the retrieved values to in situ probe measurements of ice water content (IWC), total number concentration (<em>N<sub>t</sub></em>), mass-weighted mean diameter (<em>D<sub>m</sub></em>) are 1.01, 0.97, and 1.05. The mean bias and RMSE for terminal fall velocity (<em>V<sub>t</sub></em>) are −0.02 m s⁻¹ and 0.30 m s⁻¹. Forward-simulated measurements from the retrieved profiles reproduce the actual radars and radiometer observations well, confirming the self-consistency of the current algorithm.</p> <p>A theoretical sensitivity analysis demonstrates that the radar–radiometer synergy becomes particularly effective in deep cloud layers where particle sizes are large, ensuring that the multi-sensor retrieval outperform the W-band radar-only retrieval especially deep inside clouds. These results highlight the potential of combining multi-band radar and millimeter-wave radiometer observations to advance our understanding of ice-hydrometeor microphysics in deep precipitating clouds.