Changing climate signals and the continuous world population growth requires proper hydrologic risk analysis to build and operate water resource infrastructures in a sustainable way. Although modernized computational facilities are becoming popular to understand complex systems, there is not a proper approach for the space - time analysis of extreme rainfall events. Many statistical approaches have been suggested to describe the space-time structure of rainfall; nevertheless, none of them is good enough to represent, for all observational scales, the geometrical structure observed in either rainfall time series or rainfall-derived spatial fields. This research presents a geometric approach to understand the intensity - area - duration - frequency (IADF) relationship without losing information or statistical assumptions. Moreover, this study introduces a promising conceptualization about how understand the space-time structure of rainfall via codimension functions and dynamic scaling theory.