Bridging the gaps between the GCM scales and the hydrological scales is a key issue when studying the impacts of potential climate changes on the water resources and, more generally, the links between climate variability and hydrological variability. This is especially true in tropical regions where (1) rainfall is highly variable in space and time due to its convective nature, and (2) measurements are scarce. Using high-resolution data collected in the semi arid region of Niamey, Niger, Lebel et al. [1998] have proposed a space-time model (the LBC model), allowing the disaggregation of large-scale estimates produced either from satellite images or general circulation model (GCM) outputs. The behavior of this model was shown to be globally satisfying when tested on a small number of selected Sahelian mesoscale convective complexes (SMCCs). However, to be of use in simulation studies of the impact of climate changes as predicted by GCMs or in an operational context where only satellite data are readily available, a more systematic validation was required. Also, the initial version of the model was intended at dealing with SMCCs only, leaving aside the other convective systems displaying a less coherent spatial structure. This led to develop a new version of the LBC model, presented here, characterized by the following improvements: (1) a more precise modeling of the spatial structure of the total storm rain fields by taking into account their anisotropy and using a nested covariance, (2) a better representation of the storm kinematic by dealing with arrival times of rain rather than with speeds of movement, (3) a revision of the parameters used to define the standard hyetograph which is the basis of the time disaggregation algorithm. This new version of the model has two main advantages as compared to the older one: (1) the capacity of dealing with every kind of Sahelian mesoscale convective systems (SMCSs), which account for more than 90% of the total annual rainfall in the region; (2) the possibility of using the model both in simulation and in disaggregation modes. The validation of the model is carried out by comparing the rainfall statistics at various scales of aggregation, for a set of 170 observed SMCSs (corresponding to the 1990-1993 operating period) and a set of 170 simulated SMCSs.