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<p>Aerosol–cloud interaction is the most uncertain component of the overall anthropogenic forcing of the climate, in which cloud droplet number concentration (<span class="inline-formula"><i>N</i>_d</span>) sensitivity to aerosol (<span class="inline-formula"><i>S</i></span>) is a key term for the overall estimation. However, satellite-based estimates of <span class="inline-formula"><i>S</i></span> are especially challenging, mainly due to the difficulty in disentangling aerosol effects on <span class="inline-formula"><i>N</i>_d</span> from possible confounders. By combining multiple satellite observations and reanalysis, this study investigates the impacts of (a) updraft, (b) precipitation, (c) retrieval errors, and (d) vertical co-location between aerosol and cloud on the assessment of <span class="inline-formula"><i>S</i></span> in the context of marine warm (liquid) clouds. Our analysis suggests that <span class="inline-formula"><i>S</i></span> increases remarkably with both cloud-base height and cloud geometric thickness (proxies for vertical velocity at cloud base), consistent with stronger aerosol–cloud interactions at larger updraft velocity for midlatitude and low-latitude clouds. In turn, introducing the confounding effect of aerosol–precipitation interaction can artificially amplify <span class="inline-formula"><i>S</i></span> by an estimated 21 %, highlighting the necessity of removing precipitating clouds from analyses of <span class="inline-formula"><i>S</i></span>. It is noted that the retrieval biases in aerosol and cloud appear to underestimate <span class="inline-formula"><i>S</i></span>, in which cloud fraction acts as a key modulator, making it practically difficult to balance the accuracies of aerosol–cloud retrievals at aggregate scales (e.g., 1<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M10" display="inline" overflow="scroll" dspmath="mathml"><mrow><msup><mi/><mo>∘</mo></msup><mo>×</mo><mn mathvariant="normal">1</mn><msup><mi/><mo>∘</mo></msup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="28pt" height="11pt" class="svg-formula" dspmath="mathimg" md5hash="e7e7ab1460375524fb295c27d480f6d6"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-22-7353-2022-ie00001.svg" width="28pt" height="11pt" src="acp-22-7353-2022-ie00001.png"/></svg:svg></span></span> grid). Moreover, we show that using column-integrated sulfate mass concentration (<span class="inline-formula">SO₄</span>C) to approximate sulfate concentration at cloud base (<span class="inline-formula">SO₄</span>B) can result in a degradation of correlation with <span class="inline-formula"><i>N</i>_d</span>, along with a nearly twofold enhancement of <span class="inline-formula"><i>S</i></span>, mostly attributed to the inability of <span class="inline-formula">SO₄</span>C to capture the full spatiotemporal variability of <span class="inline-formula">SO₄</span>B. These findings point to several potential ways forward to practically account for the major influential factors by means of satellite observations and reanalysis, aiming at optimal observational estimates of global radiative forcings due to the Twomey effect and also cloud adjustments.</p>