Jiao et al. (2025) Reducing uncertainty in surface solar radiation projections over the Northern Hemisphere using a hierarchical emergent constraint: Insights from CMIP6 and observation reconstruction

Identification

• Journal: Atmospheric Research
• Year: 2025
• Date: 2025-10-26
• Authors: Boyang Jiao, Yu-Cheng Su, Liya Chao, Zichen Li, Qingxiang Li, Martin Wild
• DOI: 10.1016/j.atmosres.2025.108594

Research Groups

• Guangzhou University, Guangzhou, China
• China Southern Power Grid South Electric Power Research Institute, Guangzhou, China
• College of Geographical Sciences, Inner Mongolia Normal University, Hohhot, China
• School of Atmospheric Sciences, Sun Yat-sen University, and Key Laboratory of Tropical Atmosphere−Ocean System, Ministry of Education, Zhuhai, China
• Southern Laboratory of Ocean Science and Engineering (Guangdong Zhuhai), Zhuhai, China
• Research Center for Ecology and Environment of Central Asia, Chinese Academy of Sciences, Urumqi, China
• Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland

Short Summary

This study addresses significant biases in CMIP6 model projections of surface solar radiation (SSR) over the Northern Hemisphere by proposing a Hierarchical Emergent Constraint (HEC) framework, which substantially reduces projection uncertainty and improves reliability for future solar energy assessments.

Objective

• To systematically quantify and reduce simulation biases in Coupled Model Intercomparison Project Phase 6 (CMIP6) models for surface solar radiation (SSR) projections over the Northern Hemisphere.
• To enhance the reliability of future SSR projections for renewable energy resource assessments and photovoltaic infrastructure planning.

Study Configuration

• Spatial Scale: Northern Hemisphere (NH), globally, Central Africa, North American west coast, Asian Russia, central China, South Asia, Europe, and most African regions.
• Temporal Scale: Late 20th century (historical "dimming-brightening" transition), future projections (multiple emission scenarios).

Methodology and Data

• Models used: Coupled Model Intercomparison Project Phase 6 (CMIP6) models, Hierarchical Emergent Constraint (HEC) framework.
• Data sources: Globally-benchmarked SSR dataset (SSRIH20CR), observational SSR records.

Main Results

• CMIP6 models systematically underestimate amplitudes of annual mean land SSR variations across the NH, exhibiting standard deviations of merely 0.7–1.2 W/m² and underestimation rates reaching 20 %–50 % in annual mean SSR.
• The Multi-Model Ensemble (MME) fails to reproduce the "dimming-brightening" transition observed in the late 20th century.
• The application of the HEC framework substantially reduces the magnitude of projected SSR increases and decreases globally across multiple emission scenarios.
• The HEC-constrained uncertainty range accounts for approximately 85 % of the uncertainty from unconstrained SSR simulations.
• Regionally, moderate SSR declines are projected in Central Africa, the North American west coast, Asian Russia, and central China, while more severe reductions dominate in South Asia, Europe, and most African regions.
• The HEC-corrected MME demonstrates a significant reduction in absolute bias (up to 0.26 W/m²) relative to unconstrained SSR simulations.
• The HEC enhances projection reliability through both an approximately 15 % reduction in SSR projection uncertainty and a curbed declining trend that mitigates the "hot model" bias.

Contributions

• Introduction of a novel Hierarchical Emergent Constraint (HEC) framework to systematically quantify and reduce biases in CMIP6 SSR projections.
• Significant reduction in uncertainty (approximately 15 % globally) and absolute bias (up to 0.26 W/m²) in future SSR projections over the Northern Hemisphere.
• Improved reliability of SSR projections, providing more robust inputs for solar energy yield estimation and photovoltaic infrastructure planning.
• Identification of regional differences in future SSR trends under the HEC framework.

Funding

Not explicitly mentioned in the provided text.

Citation

@article{Jiao2025Reducing,
  author = {Jiao, Boyang and Su, Yu-Cheng and Chao, Liya and Li, Zichen and Li, Qingxiang and Wild, Martin},
  title = {Reducing uncertainty in surface solar radiation projections over the Northern Hemisphere using a hierarchical emergent constraint: Insights from CMIP6 and observation reconstruction},
  journal = {Atmospheric Research},
  year = {2025},
  doi = {10.1016/j.atmosres.2025.108594},
  url = {https://doi.org/10.1016/j.atmosres.2025.108594}
}