This research investigates an alternative approach to automatically evolve the hidden temporal distribution of onset of rainfall directly from multivariate time series (MTS) data in the absence of domain experts. Temporal probabilistic modelling of the emergent situation awareness (ESA) is proposed to reveal hidden variability and dependencies over time for the onset of rainfall. Several weather parameters such as sea surface temperature, 700hPa wind anomalies, and climate indices such as El-Niño/Southern Oscillation (ENSO), etc. are analysed using the ESA technology to evolve model of temporal dependencies among these parameters. Keywords: Rainfall, Food security, Temporal probabilistic models, Statistical probabilistic models, Modelling, Water conservation, Climate changes.