2017/02/16 by Maheswaran Rathinasamy, Ankit Agarwal, Rathinasamy, Maheswaran +7
Earth and Planetary Sciences · Engineering · Environmental Science · #Atmospheric and Oceanic Physics (physics.ao-ph) #Climate variability and models #Data Analysis #Energy Load and Power Forecasting #FOS: Physical sciences #Meteorological Phenomena and Simulations #Statistics and Probability (physics.data-an)
paper · pdf · doi:10.48550/arxiv.1702.06568
openalex publication_date 2017/02/16 · openalex created_date 2017/06/05 · openalex updated_date 2026/07/28
Hydro-meteorological variables, like precipitation, streamflow are significantly influenced by various climatic factors and large-scale atmospheric circulation patterns. Efficient water resources management requires an understanding of the effects of climate indices on the accurate predictability of precipitation. This study aims at understanding the standalone teleconnection between precipitation across India and the four climate indices, namely, Niño 3.4, PDO, SOI, and IOD using partial wavelet analysis. The analysis considers the cross correlation between the climate indices while estimating the relationship with precipitation. Previous studies have overlooked the interdependence between these climate indices while analysing their effect on precipitation. The results of the study reveal that precipitation is only affected by Niño 3.4 and IOD and a non-stationary relationship exists between precipitation and these two climate indices. Further, partial wavelet analysis revealed that SOI and PDO do not significantly affect precipitation, but seems the other way because of their interdependence on Niño 3.4. It was observed that partial wavelet analysis strongly revealed the standalone relationship of climatic factors with precipitation after eliminating other potential factors. Keywords: Indian Precipitation, wavelet coherency, partial wavelet coherence, teleconnections patterns.