Short- to medium-range probabilistic precipitation forecasts over the global tropics are explored using satellite products, from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and Special Sensor Microwave/Imager (SSM/I) instruments. In addition to the conventional probability of precipitation (POP) forecast, superensemble (SE) POP forecasts are introduced and applied to the multianalysis, multicumulus-scheme, and multimodel ensemble configurations in two different horizontal resolution forecasts. It is shown that an ensemble system using a single model has a more consistent bias, which can at least partially be removed by a simple bias correction. With the aid of properly prepared ensemble members, meaningful POP forecasts have much longer forecast lead times. Results also show that a family of higher-resolution forecasts has a greater ability in removing model biases. The advantage of the SE approach is found to be evident in making POP forecasts, compared to the conventional method. The skills of SE POP are 10 to 20 percent better than those of the bias-corrected.