Existing space-time Neyman-Scott models characterize rainfall as the arrival of rain cells, clustered in time and independently distributed in space. Each cell is described as a cylinder having a random intensity (height) and random radial coverage. With this formulation it is possible to have cells with centers lying outside of a target simulation region yet having radii large enough to cover points within the region. To avoid significant boundary effects, it is necessary to include these points in the simulation. However, this can introduce inefficiency into the algorithm that is computationally restrictive. To overcome this, an efficient method is derived and demonstrated to improve computational performance.