[1] A scale-invariance analysis of rainfall retrieved during the Tropical Ocean Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA-COARE) campaign is discussed. As already found in the previous Global Atmospheric Research Program (GARP) Atlantic Tropical Experiment (GATE) rainfall data set, these new analyses of high-intensity storms confirm the evidence of scale invariance under selfsimilar space-time transformations. A simple interpretation of this space-time selfsimilarity accounting for the hierarchical organization of precipitation patterns is proposed. Finally, a downscaling model based on a log-Poisson generator is calibrated on the results of the multifractal analysis and applied to the generation of synthetic fields, reproducing observed statistical properties over a wide range of space scales and timescales.

Abstract. The development of efficient space-time rainfall downscaling procedures is highly important for the implementation of a meteo-hydrological forecasting chain operating over small watersheds. Multifractal models based on homogeneous cascade have been successfully applied in literature to reproduce space-time rainfall events retrieved over ocean, where the hypothesis of spatial homogeneity can be reasonably accepted. The feasibility to apply this kind of models to rainfall fields occurring over a mountainous region, where spatial homogeneity may not hold, is herein investigated. This issue is examined through the analysis of rainfall data retrieved by the high temporal resolution rain gage network of the Sardinian Hydrological Survey. The proposed procedure involves the introduction of a modulating function which is superimposed to homogeneous and isotropic synthetic fields to take into account the spatial heterogeneity detected in observed precipitation events. Specifically the modulating function, which reproduces the differences in local mean values of the precipitation intensity probability distribution, has been linearly related to the terrain elevation of the analysed spatial domain. Comparisons performed between observed and synthetic data show how the proposed procedure preserves the observed rainfall fields features and how the introduction of the modulating function improves the reproduction of spatial heterogeneity in rainfall probability distributions.

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Abstract. The problem of rainfall downscaling in a mountainous region is discussed, and a simple methodology aimed at introducing spatial heterogeneity induced by orography in downscaling models is proposed. This procedure was calibrated and applied to rainfall data retrieved by the high temporal resolution rain gage network of the Sardinian Hydrological Survey.