Cloud models run at 3 km resolution (typical resolution used for microwave radiative transfer applications) apart from ignoring subgrid variability (< 3 km); they also underrepresent variability of cloud particles between the scales of 3 and 15 km. In a previous study by the authors, evidence was presented that neglecting subgrid variability in modeled clouds results in considerable biases in microwave radiance computations. In this paper we present evidence that biases of the same order (−2 to −3 K for 10.7 GHz and + 4 to 5 K for 85.6 GHz) can result from underrepresented variability at scales of 3–15 km. In addition, this study reveals significant differences between modeled and observed precipitating fields at the “edges” of the storm (regions that border on zero precipitation) and documents the effects that these differences have on radiative transfer computations. It is found that biases due to underrepresented variability within the storm body are of the opposite direction to biases due to “edge” effects where partial beamfilling occurs over a field of view, and can counteract to give a misleading overall insignificant bias. However, having these two types of biases present in the (Tb-R) databases (formed by radiative transfer through 3 km modeled clouds) can have a significant effect on rainfall retrievals and can be the source of drastically different and apparently unexplainable biases from region to region and storm to storm.