Most of the recent work on rainfall data analyses and modeling has focused on either spatial or temporal variability. In this paper the structure of rainfall intermittence in space and time is investigated. Using a series of TOGA-COARE radar scans converted to maps of pixel rain rate over a tropical oceanic region of size 240 × 240 km2, regionally scale-invariant behavior of the probability distributions of wet and dry epoch durations is explored. Durations of wet and dry epochs are estimated by lengths of wet and dry spells, respectively, in time series of spatially averaged rain rate over sampled square subregions of spatial scales ranging from 120 km to 2 km. The investigation is based on sample quantiles and sample moments of the underlying marginal probability distributions, focusing on the behavior of their tails and their variation with respect to spatial scale. We find that sample tail quantiles and sample moments of wet durations exhibit power law multiscaling, while sample tail quantiles and sample moments of dry durations exhibit exponential multiscaling across the above range of scales. These findings provide new statistical diagnostic tools for validation of spatiotemporal models for rain fields.