Monsoon onset in India has always been a topic of interest for the research fraternity and various stakeholders. This study aimed to determine the monsoon onset date at the grid point scale, to obtain the trend of monsoon onset, and to unravel the spatial distribution of monsoon onset during the period 1901–2019 (especially in different climate modes). Based on observed cumulative rainfall, the piecewise linear regression model (PLRM), which employs least-squares principles, finds changepoints that signify the beginning of the monsoon season with the onset of monsoon. In this study, monsoon onset is examined with respect to several climate modes to evaluate their impact on monsoon onset. Monsoon onset is delayed in El Niño and drought years due to strong negative anomalies that are revealed by a spatial examination of monsoon onset. However, because of local atmospheric circulation impacts, there are outliers. The study also reveals areas with notable monotonic tendencies in monsoon onset, suggesting future changes in onset dates. These areas need more sophisticated frameworks for developing mitigation strategies since they should be viewed as susceptible. The comparison of the PLRM outcomes with objective methods reveals a strong correlation, confirming the accuracy of the PLRM method. Overall, the PLRM has been shown to be a useful tool for predicting the start of the monsoon on fine spatial scales and may be used in conjunction with regional climate models to anticipate the start of the monsoon in various regions of India. The results of this study could have a significant impact on regional planning and policy initiatives for sustainable development.