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<p>This study presents a new algorithm that combines W-band reflectivity measurements from the Airborne Precipitation Radar – third generation (APR-3) passive radiometric cloud optical depth and effective radius retrievals from the Research Scanning Polarimeter (RSP) to estimate total liquid water path in warm clouds and identify the contributions from cloud water path (CWP) and rainwater path (RWP). The resulting CWP estimates are primarily determined by the optical depth input, although reflectivity measurements contribute <span class="inline-formula">∼10</span> %–50 % of the uncertainty due to attenuation through the profile. Uncertainties in CWP estimates across all conditions are 25 % to 35 %, while RWP uncertainty estimates frequently exceed 100 %.</p> <p>Two-thirds of all radar-detected clouds observed during the ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) campaign that took place from 2016–2018 over the southeast Atlantic Ocean have CWP between 41 and 168 g m<span class="inline-formula">⁻²</span> and almost all CWPs (99 %) between 6 to 445 g m<span class="inline-formula">⁻²</span>. RWP, by contrast, typically makes up a much smaller fraction of total liquid water path (LWP), with more than 70 % of raining clouds having less than 10 g m<span class="inline-formula">⁻²</span> of rainwater. In heavier warm rain (i.e., rain rate exceeding 40 mm h<span class="inline-formula">⁻¹</span> or 1000 mm d<span class="inline-formula">⁻¹</span>), however, RWP is observed to exceed 2500 g m<span class="inline-formula">⁻²</span>. CWP (RWP) is found to be approximately 30 g m<span class="inline-formula">⁻²</span> (7 g m<span class="inline-formula">⁻²</span>) larger in unstable environments compared to stable environments. Surface precipitation is also more than twice as likely in unstable environments. Comparisons against in situ cloud microphysical probe data spanning the range of thermodynamic stability and meteorological conditions encountered across the southeast Atlantic basin demonstrate that the combined APR-3 and RSP dataset enable a robust joint cloud–precipitation retrieval algorithm to support future ORACLES precipitation susceptibility and cloud–aerosol–precipitation interaction studies.</p>