The ability to automatically detect spatiotemporal relationships among phenomena across scales draws new insights into the complexity of climate and weather systems. This research examines and quantifies spatial and temporal signatures of ENSO, jet streams, droughts, dry lines and severe weather outbreaks. We expand concepts of spatial dynamics in temporal GIS to the five types of phenomena across spatial and temporal scales and develop a space-time framework to represent these phenomena in GIS for spatiotemporal analysis of how changes in spatial signatures of ENSO and jet streams may spatially and temporally correlate to changes in the spatiotemporal characteristics of dry lines, droughts and severe weather outbreaks. Our premise posits the influence of ENSO on jet streams, bearings of jet streams on droughts, contribution of droughts to mesoscale convection mechanisms (i.e. dry lines), and effects of dry lines on severe weather outbreaks. We compile data to characterize the development of these phenomena over space and time and analyze their spatiotemporal relationships regarding spatial extent, shifts in position, expansion/contraction, and spatial features of these phenomena. While the research is retrospective in nature, the relationships identified offer a space-time integrative perspective to the cross-scalar complexity of climate and weather systems beyond what can be learned from trend analysis or time-step mapping of climate and weather data.