North-East Indian Monsoon rainfall (NEIMR) during October-December is of immense socio-economic importance to the agriculture-dependent population in the southeastern peninsular India. NEIMR is subject to extreme year-to-year and intra-seasonal variability that needs to be understood to enhance climate resilience. In this study, we employed hidden Markov model to characterize the spatio-temporal variations of NEIMR at pentad time step and its probability of occurrence during 1982-2014. The results indicated the dominant presence of three rainfall states during the NEIMR season, which were the wet (State-1), coastal wet (State-2), and dry (State-3) states. Seasonal total NEIMR was significantly and positively correlated with the frequency of State-1, whereas it was negatively correlated with that of State-3, indicating a crucial role of the rainfall states in determining water requirements in the southeastern peninsular India. The rainfall states were associated with distinctive atmospheric circulation and surface temperature conditions, particularly the wet (State-1) and dry (State-3) conditions. Wet conditions were characterized by enhanced cyclonic activities and increased moisture convergence at 850hPa over the southeastern peninsular India and its neighbouring oceanic regions (Bay of Bengal and Indian Ocean). In contrast, dry conditions were associated with anticyclonic circulation and reduced moisture convergence at 850hPa. The plausible physical mechanisms behind the wet (dry) condition could be that anomalous warmer (cooler) land temperature above 20 degrees N induced lower (higher) sea level pressure anomalies and drove anomalous southwesterly (northeasterly) surface winds over the NEIMR region. These anomalous surface winds and the associated lower level cyclonic (anticyclonic) circulations could enhance (suppress) moisture transport from the convergence regions over the Bay of Bengal and northern Indian Ocean into the southern peninsular India. This study revealed the pentad variability of NEIMR with the classified three rainfall states and identified the key atmospheric circulation and surface temperature conditions linked to these rainfall states.