To explore the role of cloud microphysics in a large dataset of precipitating clouds, a sixmonth dataset of satellite-derived cloud-top brightness temperatures from GOES longwave infrared (channel 4) satellite data over precipitating surface observing stations is constructed, producing 144 738 observations of snow, rain, freezing rain, and sleet. The distributions of cloud-top brightness temperatures were constructed for each precipitation type, as well as light, moderate and heavy snow and rain. The light-snow distribution has a maximum at -16°C, whereas the moderate and heavy snow distributions have a bimodal distribution around -16° to -23°C and a secondary maximum at -35° to -45°C. The light, moderate, and heavy rain, as well as the freezing rain and sleet, distributions are also bimodal with roughly the same temperature maxima, although the colder mode dominates. The colder of the bimodal peaks trends to lower temperatures with increasing rainfall intensity: -45°C for light rain, -47°C for moderate rain, and -50°C for heavy rain. Like the distributions for snow, the colder bimodal peak increases in amplitude relative to the warmer bimodal peak at heavier rainfall intensities. The steep slope in the snow distribution for cloud-top brightness temperatures warmer than -15°C is due to the combined effect of the activation of ice nuclei and the maximum growth rate for ice crystals at temperatures near -15°C. In contrast, the rain distributions have a gentle slope toward higher cloud-top brightness temperatures (-5° to 0°C) due to the warm-rain process. Finally, satellitederived cloud-top brightness temperatures are compared to coincident radiosonde-derived cloudtop temperatures. Although most difference between these two are small amplitude, some are as large as +/-60°C. The cause of these differences remains unclear, and several hypotheses are offered.3