Future changes in surface solar radiation over India: A bias-corrected and downscaled assessment of CMIP6 projections for renewable energy planning

• Bias correction and downscaling significantly improved CMIP6 solar radiation simulations, elevating correlation with ERA5 solar radiation data up to 0.94. • Higher emission scenarios (SSP2–4.5 and SSP5–8.5) show notable solar radiation reductions, exceeding –10 % by 2100 in key solar potential regions over India. • Central and southern India faces the greatest decline in solar potential, requiring reassessment of long-term Solar Photovoltaics investments. • Calls for hybrid renewable systems, advanced forecasting, and climate-informed solar planning to ensure energy resilience. Understanding future changes in surface solar radiation (SSR) is crucial for long-term renewable energy planning, especially in solar-rich countries such as India. However, high-resolution and bias-corrected SSR datasets for India remain scarce, limiting accurate assessment of future solar energy potential. In this study, we develop daily bias-corrected and statistically downscaled (BCD) dataset of SSR at a spatial resolution of 0.25°×0.25° for the Indian subcontinent. Simulations from nine Coupled Model Intercomparison Project Phase-6 (CMIP6) climate models are used for the historical period (1951–2014) and future period (2021–2100) under three Shared Socioeconomic Pathways (SSP1–2.6, SSP2–4.5, SSP5–8.5). The BCD was implemented using the Empirical Quantile Mapping (EQM) method at each fine-resolution grid point, improving local-scale variability representation. ERA5’s surface solar radiation downward (SSRD) is used as the reference dataset to downscale, bias correct, and validate the models. Evaluation of BCD dataset against observations showed substantial performance improvement, with correlation coefficients increasing from 0.65 to 0.81 (raw) to 0.89–0.94 (corrected) and reducing root mean square error across all models. These improvements in dataset reliability lay a strong foundation for analysing future SSR dynamics under different climate scenarios. Future projections indicate a progressive decline in SSR with increasing emission intensity: modest changes under SSP1–2.6, with slight positive anomalies over parts of northern India, and pronounced reductions of up to –10 % under SSP2–4.5 and SSP5–8.5, particularly over central, southern, and eastern India. Decadal trends reveal average declines of –0.11 %, –0.52 %, and –0.60 % per decade under SSP1–2.6, SSP2–4.5, and SSP5–8.5, respectively, with a temporary slowdown in mid-century (2041–2060) under SSP2–4.5 followed by renewed intensification. The resulting high-resolution BCD dataset not only represents a technical advancement in the robust downscaling of CMIP6 SSR for India but also provides a practical resource to guide solar park siting, optimize grid integration strategies, and support climate-resilient energy policy development.

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Journal
Energy and Climate Change
Published
2025-09-04
DOI
https://doi.org/10.1016/j.egycc.2025.100213
Primary Topic
Climate variability and models
Type
article
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article

Future changes in surface solar radiation over India: A bias-corrected and downscaled assessment of CMIP6 projections for renewable energy planning

Ashwin Vijay Jadhav, Rohini Bhawar
Energy and Climate Change
Climate variability and models
article

Future changes in surface solar radiation over India: A bias-corrected and downscaled assessment of CMIP6 projections for renewable energy planning

Ashwin Vijay Jadhav, Rohini Bhawar
article en

Abstract

• Bias correction and downscaling significantly improved CMIP6 solar radiation simulations, elevating correlation with ERA5 solar radiation data up to 0.94. • Higher emission scenarios (SSP2–4.5 and SSP5–8.5) show notable solar radiation reductions, exceeding –10 % by 2100 in key solar potential regions over India. • Central and southern India faces the greatest decline in solar potential, requiring reassessment of long-term Solar Photovoltaics investments. • Calls for hybrid renewable systems, advanced forecasting, and climate-informed solar planning to ensure energy resilience. Understanding future changes in surface solar radiation (SSR) is crucial for long-term renewable energy planning, especially in solar-rich countries such as India. However, high-resolution and bias-corrected SSR datasets for India remain scarce, limiting accurate assessment of future solar energy potential. In this study, we develop daily bias-corrected and statistically downscaled (BCD) dataset of SSR at a spatial resolution of 0.25°×0.25° for the Indian subcontinent. Simulations from nine Coupled Model Intercomparison Project Phase-6 (CMIP6) climate models are used for the historical period (1951–2014) and future period (2021–2100) under three Shared Socioeconomic Pathways (SSP1–2.6, SSP2–4.5, SSP5–8.5). The BCD was implemented using the Empirical Quantile Mapping (EQM) method at each fine-resolution grid point, improving local-scale variability representation. ERA5’s surface solar radiation downward (SSRD) is used as the reference dataset to downscale, bias correct, and validate the models. Evaluation of BCD dataset against observations showed substantial performance improvement, with correlation coefficients increasing from 0.65 to 0.81 (raw) to 0.89–0.94 (corrected) and reducing root mean square error across all models. These improvements in dataset reliability lay a strong foundation for analysing future SSR dynamics under different climate scenarios. Future projections indicate a progressive decline in SSR with increasing emission intensity: modest changes under SSP1–2.6, with slight positive anomalies over parts of northern India, and pronounced reductions of up to –10 % under SSP2–4.5 and SSP5–8.5, particularly over central, southern, and eastern India. Decadal trends reveal average declines of –0.11 %, –0.52 %, and –0.60 % per decade under SSP1–2.6, SSP2–4.5, and SSP5–8.5, respectively, with a temporary slowdown in mid-century (2041–2060) under SSP2–4.5 followed by renewed intensification. The resulting high-resolution BCD dataset not only represents a technical advancement in the robust downscaling of CMIP6 SSR for India but also provides a practical resource to guide solar park siting, optimize grid integration strategies, and support climate-resilient energy policy development.

Energy and Climate ChangeVol. 6
Savitribai Phule Pune University (IN)
Openalex Percentile: Top 77%
Climate variability and models
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