Tu et al. (2026) Estimating hourly surface global and diffuse solar radiation across China using virtual radiation station networks

Identification

• Journal: Remote Sensing of Environment
• Year: 2026
• Date: 2026-09-29
• Authors: Yuhong Tu, Xin Yang, Hong Tang, Haoze Shi
• DOI: 10.1016/j.rse.2026.115713

Research Groups

State Key Laboratory of Earth Surface Processes and Disaster Risk Reduction, Faculty of Geographical Science, Beijing Normal University

Short Summary

This study developed a two-stage strategy to estimate hourly surface global and diffuse solar radiation across China using virtual radiation station networks, achieving superior performance with RMSE (R2) of 82.55 W/m2 (0.91) for Rs and 64.11 W/m2 (0.73) for Rdif.

Objective

• Estimate high-resolution surface downward global and diffuse solar radiation across China using virtual radiation station networks.

Study Configuration

• Spatial Scale: National scale, covering the entire territory of China.
• Temporal Scale: Hourly resolution, allowing for accurate estimation of diurnal variations in solar radiation.

Methodology and Data

• Models used:
  • Two-step Virtual Radiation Network Estimators (VRNE) with a self-attention mechanism.
  • Pixel-wise Mapping Radiation Estimator (PMRE).
• Data sources:
  • Satellite data.
  • Reanalysis data.
  • Sunshine duration observations.

Main Results

• The developed two-stage strategy achieved superior performance in estimating Rs and Rdif, outperforming widely used global radiation products.
• The estimates had RMSE (R2) of 82.55 W/m2 (0.91) for Rs and 64.11 W/m2 (0.73) for Rdif.

Contributions

• This study addressed the limitation of existing studies by incorporating spatial-contextual information among stations and sunshine duration observations.
• The developed two-stage strategy improved the spatial generalization and reduced systematic magnitude biases prevalent in widely used global radiation products.

Funding

• This research was funded by the State Key Laboratory of Earth Surface Processes and Disaster Risk Reduction, Faculty of Geographical Science, Beijing Normal University.

Citation

@article{Tu2026Estimating,
  author = {Tu, Yuhong and Yang, Xin and Tang, Hong and Shi, Haoze},
  title = {Estimating hourly surface global and diffuse solar radiation across China using virtual radiation station networks},
  journal = {Remote Sensing of Environment},
  year = {2026},
  doi = {10.1016/j.rse.2026.115713},
  url = {https://doi.org/10.1016/j.rse.2026.115713}
}