Decoding of long-term spatio-temporal precipitation dynamics over India: Insights from 115 years of meteorological data
Year: 2025
Type: article
Abstract: Understanding precipitation variability is crucial for assessing climate change impacts on ecosystems, agriculture, and water resources. This study examines the past 115 years of long-term rainfall data across 34 meteorological subdivisions in India using statistical techniques, including the double exponential model (DEM), Mann-Kendall test, and Generalized Extreme Value (GEV) analysis. The key findings are: (1) A significant shift in rainfall patterns occurred post-1945 and 1990, confirmed by Pettitt’s test and the Mann-Whitney U test (p = 0.0025), with α values declining from 2.2 to 1.5 cm and β values fluctuating between 100 and 300 cm, indicating increased rainfall intensity; (2) Extreme rainfall events (≥90 cm/day) are concentrated in coastal regions (Kerala, Karnataka, Maharashtra) and northeastern states (Assam, Manipur, Shillong), as validated by GEV-based return period analysis; (3) Monsoon season variability accounts for 55–65 % of rainfall fluctuations, driven by short-term oscillations such as oscillations El Niño-Southern Oscillation (ENSO), and Indian Ocean Dipole (IOD), while long-term climatic trends contribute 35–45 % of the variance; (4) Sen’s slope analysis reveals increasing monsoon rainfall trends in Jammu & Kashmir, Punjab, Rajasthan, and Gujarat, whereas parts of Maharashtra and northeastern India exhibit a decline. These findings provide critical insights for water resource management, disaster preparedness, and climate adaptation strategies, supporting evidence-based policymaking for sustainable development.
Authors: Deepak Soni, Avinash Dass, Pramod Kamble, Ramesh Kumar
Language: English
Subfield: Global and Planetary Change
Field: Environmental Science
Domain: Physical Sciences
SDG: Climate action
Open Access status: gold
Estimated APC paid: $2,150
OpenAlex ID: W4409252432