The feedback of topsoil moisture (SM) content on convective clouds and precipitation is not well understood and represented in the current generation of coupled cloud physics and land-surface models. Here, we use functional decomposition of satellite-derived SM (SMAP/L4) and cloud vertical profiles (CVP: GPM/DPR/L2A) in the central US to quantify the relationship between SM and the vertical distribution of cloud water. High-dimensional model representation disentangles the contributions of SM and other land-surface and atmospheric variables to the CVP. Results show the sign and strength of this feedback varies with cloud height and time lag and displays a large spatial variability. Positive anomalies in the antecedent 7-hour SM and land-surface temperature can increase reflectivity up to 4 dBZ in the lower atmosphere (1-3 km above the surface). The presented approach brings new insights into observational understanding of SM-precipitation feedback and possesses the potential for diagnosing cloud models regarding land-atmosphere coupling representation.