Realistic rainfields that represent storms with a known return period are r
equired as input to design calculations for hydrological projects that cove
r a wide range of hydrological scales. The current standard practice is to
assume either that the storm is uniform in time and space or that it varies
in some very simple manner. Multiaffine models of rainfall, based on the c
oncept of a multiplicative cascade, provide the possibility of generating a
stochastic series of space and time rainfall that reproduces the observed
behavior. The spatial distribution of a field of instantaneous rain rates i
s modeled using the multiplicative cascade approach. The temporal developme
nt of the cascade weights at each level in the cascade is modeled with a si
mple autoregressive ARMA(1,1) model where the parameters vary in a systemat
ic manner with scale. The model is verified using rain fields produced by a
monsoonal depression that passed over a weather radar at Darwin, Australia
. Radar data for the event were used to estimate the model parameters. The
model was able to reproduce the observed temporal and spatial correlation f
unctions over a range of scales, and the probability distributions over a r
ange of scares, for both the instantaneous and the hourly accumulations.