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<p>Reliable regional climate projections are essential for adaptation in climate-sensitive regions such as Odisha, India. This study develops an integrated framework combining Expert Team on Climate Change Detection and Indices (ETCCDI)-based extremes, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), and Monte Carlo sensitivity analysis to evaluate and optimise 35 bias-corrected Global Climate Models (GCMs) from the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP-CMIP6). The optimised Multi-Model Ensemble (MME) reproduces historical temperature and precipitation patterns (1985–2014) with modest bias and strong seasonal agreement, and is applied to projections under SSP2-4.5 and SSP5-8.5 (2015–2100). Results indicate progressive warming: maximum and minimum temperatures increase by ~ 1.7&#xa0;°C under SSP2-4.5 and ~ 3.3–3.4&#xa0;°C under SSP5-8.5 by late century, with summer days (SU) rising by ~ 20–46&#xa0;days and tropical nights (TR) by up to ~ 112&#xa0;days. The extreme temperature range (ETR) widens significantly under SSP5-8.5. Precipitation increases are largest during winter and post-monsoon seasons, while monsoon-season changes remain small and slightly negative under SSP2-4.5. Very wet (R95pTOT) and extremely wet (R99pTOT) precipitation increase by ~ 3% and ~ 2% under SSP2-4.5, and by ~ 5% and ~ 4% under SSP5-8.5, indicating a growing contribution of extreme rainfall events to annual precipitation totals. Northern and coastal Odisha show higher precipitation increases, while inland regions experience stronger warming and enhanced heat stress. The framework provides a transparent and reproducible basis for regional climate assessment.</p>

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Optimising CMIP6 Multi-model ensembles using ETCCDI–TOPSIS–Monte carlo framework for reliable climate projections over Odisha, India

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  • 发表日期：

    2026年6月30日

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  • Nishikanta Kar,
  • Sarat Chandra Sahu

摘要

Reliable regional climate projections are essential for adaptation in climate-sensitive regions such as Odisha, India. This study develops an integrated framework combining Expert Team on Climate Change Detection and Indices (ETCCDI)-based extremes, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), and Monte Carlo sensitivity analysis to evaluate and optimise 35 bias-corrected Global Climate Models (GCMs) from the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP-CMIP6). The optimised Multi-Model Ensemble (MME) reproduces historical temperature and precipitation patterns (1985–2014) with modest bias and strong seasonal agreement, and is applied to projections under SSP2-4.5 and SSP5-8.5 (2015–2100). Results indicate progressive warming: maximum and minimum temperatures increase by ~ 1.7 °C under SSP2-4.5 and ~ 3.3–3.4 °C under SSP5-8.5 by late century, with summer days (SU) rising by ~ 20–46 days and tropical nights (TR) by up to ~ 112 days. The extreme temperature range (ETR) widens significantly under SSP5-8.5. Precipitation increases are largest during winter and post-monsoon seasons, while monsoon-season changes remain small and slightly negative under SSP2-4.5. Very wet (R95pTOT) and extremely wet (R99pTOT) precipitation increase by ~ 3% and ~ 2% under SSP2-4.5, and by ~ 5% and ~ 4% under SSP5-8.5, indicating a growing contribution of extreme rainfall events to annual precipitation totals. Northern and coastal Odisha show higher precipitation increases, while inland regions experience stronger warming and enhanced heat stress. The framework provides a transparent and reproducible basis for regional climate assessment.