Indian monsoon and its links with global and local climate variables.

Altered precipitation in changing environment is a significant issue, which may result in various hazards, including flooding. The complex and changeable Indian rainfall system relies on meteorological and oceanic phenomena. There is a need to understand these changes and attribute their cause. However, an obvious conclusion cannot be drawn using the linear trend methodologies used in previous research. Hence, the changing characteristics of the precipitation should be explored using a non-linear trend approach for better understanding and to determine the non-linear changes in the climate system. In this study, we used the non-linear method for finding the Spatio-temporal variation of regional trends in precipitation (using 0.25°×0.25° gridded datasets) and other local and global climatic variables (DTR, LTA, GTA, ENSO, IOD, MEI) for the period of 69 years (1951-2019). Here, Ensemble Empirical Mode Decomposition (EEMD) is used to decompose the Annual Maximum Precipitation (AMP) and potential climatic variables into a finite number of Intrinsic Mode Functions (IMF). The final residual component explains the raw data's slow varying characteristics (trend). The regional evolution of the precipitation trend shows an increasing trend in central India (Rajasthan, the west part of Gujarat, and some grids of Sikkim). In the case of DTR, decreasing trend is observed in the central part of southern Gujarat, Rajasthan, and West Bengal, and an increasing trend in the sub-tropical forest on the North-East, West and East coast. However, the global climatic factors (ENSO, GTA, IOD, and MEI) depict an increasing trend. The relationship between AMP and DTR at specific grids shows an inverse and direct connection between AMP and LTA. This clearly indicates that the global and local factors are working in tandem.