Multiscale teleconnection analysis of rainfall patterns over Calicut, India using wavelet coherence

Understanding the association of climatic oscillations (COs) and meteorological parameters (MPs) with rainfall is of considerable significance in the management of water resources. This study used bivariate wavelet coherence (BWC), partial wavelet coherence (PWC) and multiple wavelet coherence (MWC) formulations for investigating the multiscale coherence of monthly mean rainfall of Calicut, Kerala, India with diverse sets of COs and local MPs. Firstly, the multiscale association between rainfall of 1970 and 2019 with four COs, viz., El Niño Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), Indian Ocean Dipole (IOD) and North Atlantic Oscillation (NAO) are investigated using different WC formulations. The BWC and PWC analyses detected PDO and NAO as the significant COs influencing rainfall of Calicut, strongly modulated by ENSO and IOD. MWC analysis with 11 combinations of COs revealed the highest coherence for ENSO–IOD and ENSO–PDO–NAO, indicating an equally strong influence of different COs upon the rainfall of Calicut. Further, the teleconnections of rainfall with local MPs, viz., maximum temperature (T_max), minimum temperature (T_min), wind speed (U) and evaporation (E) over Calicut are also analyzed. The BWC analysis detected annual periodicity in all the time series, with an additional band at the scale of six months in T_min series. The coherence strength quantified in terms of average wavelet coherence (AWC) and percentage of significant coherence (PSC) showed that evaporation was the most significant MP (AWC of 0.66 and PSC of 54%) modulated strongly by wind speed. The MWC analysis of rainfall with MPs displayed the highest coherence for T_min–E and U–T_min–E combinations in the rainfall of Calicut.