In this presentation the scaling properties of rainfall time-series generated by a climate model are analysed by means of a multifractal characterization based on the "universal multifractal" formalism. The analysed data are the rainfall daily time-series over France computed in a simulation over the period 1860-2100 by the climate model CNRM-CM3 of Meteo-France in a coupled IPCC climate scenario (A2). We quantify the scaling variability of the simulated rainfall with the help of a few relevant multifractal exponents characterizing the intermittency and multifractality of the field. These multifractal exponents are determined by the Double Trace Moment (DTM) which shows a scaling range from one day to about 16 days. The opposite trends found in the evolution of the intermittency and multifractality exponents, have contradictory effects on the evolution of the extremes. However, a refined analysis shows that due to the dominant effect of intermittency increase, we may expect an effective increase of rainfall extremes for the next hundred years.