Hydroclimatic Signatures of ENSO over India Understanding Rainfall Variability and Regional Sensitivity
V. S. Yadav
Department of Farm Engineering, Institute of Agricultural Sciences, Banaras Hindu University Varanasi-221005, UP, India.
Archana Kaushal *
Department of Soil and Water Engineering, College of Agricultural Engineering, JNKVV, Jabalpur-482004, (MP), India.
Anoop Patel
Department of Soil and Water Engineering, College of Agricultural Engineering, JNKVV, Jabalpur-482004, (MP), India.
Lokesh Patel
National Institute of Hydrology, Central India Hydrology Regional Centre, Bhopal - 462042, MP, India.
Pushpanjali Kumari
Department of Civil Engineering, Central University of Jharkhand, Ranchi 835205, India.
Samikshya Panda
Department of Farm Engineering, Institute of Agricultural Sciences, Banaras Hindu University Varanasi-221005, UP, India.
Ankit Patel
Department of Farm Engineering, Institute of Agricultural Sciences, Banaras Hindu University Varanasi-221005, UP, India.
*Author to whom correspondence should be addressed.
Abstract
This study investigates the relationship between the El Niño–Southern Oscillation (ENSO) and regional rainfall variability across India using high-resolution gridded rainfall data and the Nino 3.4 index for the period 1951–2023. The Pearson Correlation Coefficient (PCC) was employed to assess the strength and direction of the association between rainfall anomalies and ENSO phases (El Niño and La Niña). Results reveal a strong negative correlation during El Niño years, indicating widespread rainfall deficiency, while La Niña years generally correspond to enhanced precipitation across most regions. Among the five studied regions, North India exhibited the highest negative correlation (r = -0.65) with El Niño, reflecting its pronounced vulnerability to monsoon weakening, whereas South India showed the strongest positive correlation (r = 0.55) with La Niña, suggesting greater rainfall enhancement. Central, East, and West regions displayed moderate correlations, highlighting spatial variations in ENSO influence. The analysis underscores that ENSO remains a major large-scale climate driver affecting India’s rainfall distribution, though its effects are region-specific and modulated by local climatic factors. Understanding these spatial dynamics is essential for improving seasonal monsoon forecasts, agricultural planning, and drought preparedness, thereby contributing to more resilient water resource management strategies under climate variability.
Keywords: El Niño, La Niña, rainfall anomaly, Indian monsoon, pearson correlation coefficient, drought