Rainfall downscaling in a space-time multifractal framework

A space-time multifractal analysis on radar rainfall sequences selected from the Global Atmospheric Research Program Atlantic Tropical Experiment database is presented. It is shown that space-time rainfall can be considered with a good approximation to be a self-similar multifractal process, so that a multifractal analysis can be carried out assuming Taylor's hypothesis to hold for rainfall over a wide range of spatial and temporal scales. The advection velocity needed to rescale the time dimension is estimated using different tracking techniques. On each selected rainfall sequence, a very good scaling is observed for spatial scales ranging from 4 to 256 km and for timescales from 15 min to 16 hours. A recently developed scale-covariant multifractal model is then reformulated for numerical simulation of space-time rainfall fields. The two parameters of the log-Poisson distribution used as cascade generator within the model are systematically estimated from each selected rainfall sequence, and the dependence of one of these parameters on the large-scale rain rate is highlighted. The model is then applied to disaggregate large-scale rainfall, and some comparisons between synthetically downscaled and observed rainfall are discussed