Gangwar et al. (2026) Consistent increase in Southwest Monsoon rainfall in Telangana, India: insights from bias-corrected CMIP6 simulations

Identification

• Journal: Theoretical and Applied Climatology
• Year: 2026
• Date: 2026-03-12
• Authors: Amit Gangwar, K. Koteswara Rao, Dandi A. Ramu, A. Dharma Raju, Gopi Krishna Podapati
• DOI: 10.1007/s00704-026-06100-6

Research Groups

• Centre for Earth, Ocean and Atmospheric Sciences, School of Physics, University of Hyderabad, Hyderabad, Telangana, India
• National Centre of Meteorology, Abu Dhabi, United Arab Emirates
• India Meteorological Department, Ministry of Earth Sciences, Hyderabad, India

Short Summary

This study projects future changes in Southwest Monsoon rainfall in Telangana, India, using statistically downscaled and bias-corrected CMIP6 models, finding a consistent and significant increase in the frequency and intensity of extreme rainfall events by the end of the 21st century under both moderate and high emission scenarios.

Objective

• To investigate the spatial and temporal variations of mean and extreme Southwest Monsoon rainfall in Telangana, India, under present and future climate scenarios (SSP2-4.5 and SSP5-8.5) using statistically downscaled and bias-corrected CMIP6 multi-model mean projections.

Study Configuration

• Spatial Scale: Telangana, India (semi-arid region in southern India), at a high horizontal resolution of 0.25° latitude × 0.25° longitude.
• Temporal Scale: Historical (1951–2014 for models, 1985–2014 for baseline/observations), Near Future (2021–2050), and Far Future (2071–2100), focusing on the Southwest Monsoon season (June to September - JJAS) and individual months.

Methodology and Data

• Models used: Multi-Model Mean (MMM) from 13 CMIP6 models, statistically downscaled using the Empirical Quantile Mapping (EQM) technique, and bias-corrected.
• Data sources:
  • Statistically downscaled and bias-corrected daily rainfall data from CMIP6 model simulations.
  • Daily gridded rainfall dataset from the India Meteorological Department (IMD) at 0.25° latitude × 0.25° longitude for the baseline period (1985–2014).
  • Shared Socioeconomic Pathways (SSP) scenarios: SSP2-4.5 (moderate emissions) and SSP5-8.5 (high emissions).
  • Eight extreme precipitation indices (EPIs): Consecutive Dry Days (CDD), Number of Heavy Precipitation Days (R10mm), Rainy Days, Precipitation on Very Wet Days (R95pTOT), Maximum 1-day rainfall (Rx1day), Maximum 5-day rainfall (Rx5day), Total Wet-Day Precipitation (PRCPTOT), and Simple Daily Intensity Index (SDII).

Main Results

• The Multi-Model Mean (MMM) of CMIP6 models effectively reproduces the annual rainfall cycle and spatial distribution over Telangana, showing a high pattern correlation of 0.98 with observed IMD data for the JJAS season.
• Near-future projections (2021–2050) indicate a significant increase in mean rainfall during July and August under both SSP2-4.5 and SSP5-8.5 scenarios.
• Far-future projections (2071–2100) show moderate increases in JJAS rainfall under SSP2-4.5 and substantial increases, potentially up to 50% in specific areas, under SSP5-8.5.
• A slight decrease in the number of rainy days is projected for the near future, but a significant increase (5% to 25%) is expected in the far future under both SSP scenarios.
• All precipitation extreme indices (Rainy days, SDII, Rx1day, Rx5day, PRCPTOT, R95pTOT), except Consecutive Dry Days (CDD), are projected to show a significant rise, particularly under the high-emission SSP5-8.5 scenario in the far future.
• Rx1day rainfall is projected to surge by over 40% across most of Telangana under SSP5-8.5 in the far future.
• The Simple Daily Intensity Index (SDII) is expected to increase by 5–10% in the near future and by over 40% under SSP5-8.5 in the far future.
• Consecutive Dry Days (CDD) are projected to rise significantly in the near future (e.g., June by ~150%, September by ~100% under SSP5-8.5), but show a notable decline in the far future, suggesting a rapid decrease in dry days by the end of the 21st century.
• Extreme rainfall events, particularly R10mm and R95pTOT, are expected to intensify significantly, with R95pTOT exceeding 200% in August and September in the far future under SSP5-8.5.
• The probability density function (PDF) analysis suggests a shift towards higher rainfall intensities and a decrease in low-intensity events across all monsoon months in the far future under both SSP scenarios.

Contributions

• This study provides the first assessment of future rainfall extremes over the semi-arid Telangana region using the latest high-resolution, bias-corrected CMIP6 multi-model mean projections under SSP scenarios for the summer monsoon season.
• It offers unique insights into the spatial and temporal variations of mean and extreme rainfall in Telangana under present and future climate conditions.
• The research highlights the disproportionate increase in high-intensity rainfall indices compared to mean rainfall, linking it to the non-linear relationship between warming and atmospheric moisture availability (Clausius-Clapeyron relation).
• The findings underscore the critical hydrological implications for flood management, infrastructure resilience, and water resource planning in Telangana, emphasizing the need for climate-resilient strategies.

Funding

No Funding available.

Citation

@article{Gangwar2026Consistent,
  author = {Gangwar, Amit and Rao, K. Koteswara and Ramu, Dandi A. and Raju, A. Dharma and Podapati, Gopi Krishna},
  title = {Consistent increase in Southwest Monsoon rainfall in Telangana, India: insights from bias-corrected CMIP6 simulations},
  journal = {Theoretical and Applied Climatology},
  year = {2026},
  doi = {10.1007/s00704-026-06100-6},
  url = {https://doi.org/10.1007/s00704-026-06100-6}
}