A stochastic rainfall simulator based on the concept of “dry drift” is proposed. It is characterized by a new and nonstationary representation of rainfall in which the average rain rate (in log-space) depends on the distance to the closest surrounding dry areas. The result is a more realistic transition between dry and rainy areas and a better distribution of low and high rain rates inside the simulated rainy areas. The proposed approach is very general and can be used to simulate both unconditional and conditional rain rate time series, two-dimensional fields, and space-time fields. The parameterization is intuitive and can be done using time series and/or radar rain-rate maps. Several examples illustrating the simulator's capabilities are given. The results show that the simulated time series and rain rate fields look realistic and that they are difficult to distinguish from real observations.