Time–frequency characterization of seasonal temperature in India and teleconnection of temperature with atmospheric oscillation indices

Abstract

The present study focuses on characterizing the time–frequency aspects of seasonal temperatures in India by integrating the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) algorithm with the Hilbert–Huang transform (HHT) decomposition method. The investigation also explores the connections between maximum temperature (T_max) and minimum temperature (T_min) with global climate oscillations, such as the El Nino Southern Oscillation (ENSO), Sunspot Number (SN), and Pacific Decadal Oscillations (PDO). The findings indicate that intra and inter-decadal modes play a pivotal role in influencing temperature series across various seasons, with notable changes observed in the amplitudes of inter-decadal modes for seasonal T_min and T_max. The analysis of intrinsic mode functions (IMFs) reveals that IMF2 closely align to ENSO with a periodicity of 5–7 years, IMF3 to the sunspot cycle with a frequency of approximately 11 years, and IMF5 to PDO with a long periodicity exceeding 60 years. The association between the IMF components of T_min and T_max temperature series and the three climate indices is most evident for low-frequency modes, demonstrating a consistent evolution of trend components.