On the relationship of climatic and monsoon teleconnections with monthly precipitation over meteorologically homogenous regions in India: Wavelet & global coherence approaches

Abstract

The hydro-climatic variables are greatly influenced by the large-scale phenomena at global and regional scales. The present study attempts to characterise the influence of large-scale climatic oscillations on the monthly precipitation over meteorologically homogeneous regions in India. To accomplish the study, the monthly precipitation over selected six different regions are obtained during 1951–2015 and correlations with the eight large-scale climatic oscillations namely, Indian Ocean Dipole (IOD), Sea Surface Temperature (SST), Multivariate ENSO Index (MEI), Southern Oscillation Index (SOI), Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), Arctic Oscillation (AO), and Indian Summer Monsoon Index (ISMI) are examined using wavelet and global coherence. The outcomes from the analysis suggest that though other climatic indices have noticeable effects on the monthly precipitation over India, the ISMI is the most effective climatic teleconnection. The predominant and effective period of ISMI is at intra-annual scale influencing Central Northeast India (CNI), Peninsular India (PI), and West Central India (WCI), while the major effective period of IOD is in between 8 and 16 months. For the El Niño–Southern Oscillation (ENSO) indices like SST, SOI, and MEI the most prominent period is noticed during 20 to 54 months time scale over different parts of India. The phase difference is not uniform between the studied climatic oscillations and monthly precipitation across the country. For long terms of ISMI, an in-phase situation is observed over all the meteorologically homogenous regions in India. The present study advocates that the wavelet and global coherence approaches are very powerful tools to analysing the relationship between multiple time-series in a time-frequency space and its application in hydrology enables the water resources managers in developing better understanding of meteorological connections with the large-scale low frequency climatic oscillations. © 2020 Elsevier B.V.