The team assembled in-situ observations from seven radiation stations along the corridor and compared them with the ERA5-Land reanalysis for the historical period 1985 to 2014. The reanalysis reproduced observed surface solar radiation with domain-wide correlations exceeding 0.96 and root mean square errors below 86 megajoules per square metre. The historical record revealed sharp regional contrasts: southern and northern Pakistan averaged 7,500 to 8,400 megajoules per square metre, while central areas recorded 6,600 to 7,500 megajoules per square metre, a pattern that reflects the corridor’s varied terrain and climate zones.

To look forward, the researchers used 11 models from the Coupled Model Intercomparison Project Phase 6 under three Shared Socioeconomic Pathways: SSP1-2.6, a low-emissions scenario; SSP2-4.5, an intermediate pathway; and SSP5-8.5, a high-emissions scenario. Because raw climate model output often deviates systematically from observed radiation, the team applied the MBCn multivariate bias-correction algorithm. After correction, all 11 models achieved correlations above 0.94 with root mean square errors below 53 megajoules per square metre, and the multi-model ensemble mean reduced the error further, to 28 megajoules per square metre.

The corrected ensemble produced consistent increases in surface solar radiation across all three scenarios for the period 2051 to 2100. Under SSP1-2.6, radiation is projected to rise by 50 to 150 megajoules per square metre; under SSP2-4.5, by 100 to 200 megajoules per square metre; and under SSP5-8.5, by 150 to 300 megajoules per square metre. The spread across scenarios indicates that the magnitude of future brightening depends strongly on the emissions pathway the world follows, with the high-emissions case roughly doubling the projected gain compared with the low-emissions case.

Equally important for planners is where the uncertainty in these projections comes from. The study decomposed projection uncertainty into its constituent parts and found that model uncertainty, meaning differences among the individual climate models, dominated across all future periods, accounting for 56.4 to 78.7 percent of the total. The interaction between models and scenarios grew substantially over time, reaching 33.4 percent by 2051 to 2100, while scenario uncertainty on its own remained relatively small throughout every period investigated. In practical terms, the choice of climate model matters more for projecting corridor radiation than the choice of emissions scenario, at least through the second half of the century.

The authors emphasize that the bias-corrected multi-model ensemble dataset they produced is intended as a practical input for real-world decisions. Potential applications include siting photovoltaic power plants, modeling energy systems that must balance solar output against other sources, and planning climate-resilient infrastructure along the corridor, where rapid economic growth has intensified demand for reliable, high-resolution radiation projections. Because the projections are model-based estimates spanning broad regions and multi-decade averages, they describe expected large-scale trends rather than site-specific guarantees, and the identified model uncertainty should be carried into any downstream engineering or investment analysis.

Subject of Research: Future projection of solar radiation along the China–Pakistan economic corridor under diverse emission scenarios

Article Title: Future projection of solar radiation along the China–Pakistan economic corridor under diverse emission scenarios

Article References: Mamtimin, A., Aihaiti, A., Zhang, H., Sun, Z., Peng, J., Liu, H., Sayit, H., Liu, J., Wang, Y., Luo, Q., & Wang, D. (2026). Future projection of solar radiation along the China–Pakistan economic corridor under diverse emission scenarios. Theoretical and Applied Climatology, 157(11), Article 750. https://doi.org/10.1007/s00704-026-06678-x

Image Credits: AI Generated

DOI: 10.1007/s00704-026-06678-x

Keywords: Future, projection, solar, radiation, along, China, Pakistan, economic, corridor, under, diverse, emission