Zhang et al. (2025) Assessment of WRF-Solar and WRF-Solar EPS Radiation Estimation in Asia Using the Geostationary Satellite Measurement

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Identification

• Journal: Remote Sensing
• Year: 2025
• Date: 2025-12-09
• Authors: Haoling Zhang, Lei Li, Xindan Zhang, Shuhui Liu, Yu Zheng, Ke Gui, Jingrui Ma, Huizheng Che
• DOI: 10.3390/rs17243970

Research Groups

Not explicitly mentioned in the provided text. However, the research involves expertise in atmospheric science, numerical weather prediction, and solar energy forecasting.

Short Summary

This study evaluates the short-term performance of the WRF-Solar model and its ensemble version for global horizontal irradiance (GHI) and direct horizontal irradiance (DIR) over East Asia, revealing systematic overestimation for GHI and regional biases for DIR, with limited improvement from the ensemble, necessitating refinements in cloud-aerosol parameterizations.

Objective

• To evaluate the short-term (<36 hours) forecasting performance of the Weather Research and Forecasting model (WRF-Solar) and its ensemble version (WRF-Solar EPS) for global horizontal irradiance (GHI) and direct horizontal irradiance (DIR) over East Asia.

Study Configuration

• Spatial Scale: East Asia, with specific error patterns identified in northwest China, North China Plain, Tibetan Plateau, southern China, Indo-China Peninsula, and southeast China.
• Temporal Scale: Short-term forecasts (<36 hours), evaluated over a one-year period from December 2019 to November 2020.

Methodology and Data

• Models used: Weather Research and Forecasting model (WRF-Solar), WRF-Solar Ensemble Prediction System (WRF-Solar EPS).
• Data sources: Geostationary satellite retrievals (used for validation).

Main Results

• Both WRF-Solar and WRF-Solar EPS effectively capture GHI spatial patterns but exhibit systematic overestimation, with biases ranging from 17.27 W/m² to 17.68 W/m².
• Peak GHI errors occur in northwest China and the North China Plain. Temporal mismatches were observed, with maximum bias in winter-spring and maximum RMSE/MAE in summer, potentially linked to seasonal variability in aerosol and cloud error signatures.
• For DIR, regional biases are prevalent: overestimation in the Tibetan Plateau and northwest China, and underestimation in southern China and the Indo-China Peninsula.
• DIR errors (RMSE and MAE) are larger than for GHI, with peaks in southeast and northwest China, likely due to poor cloud–aerosol simulations.
• WRF-Solar EPS showed no significant bias reduction but provided modest RMSE/MAE improvements during summer–autumn, particularly in southeast China, indicating limited enhancement of short-term predictive stability.

Contributions

• Provides a comprehensive, year-long evaluation of WRF-Solar and WRF-Solar EPS for short-term GHI and DIR forecasting over the climatically complex East Asia region.
• Identifies systematic biases and distinct spatial and temporal error patterns for both GHI and DIR, attributing them to deficiencies in cloud–aerosol parameterizations.
• Quantifies the limited benefit of the ensemble approach (WRF-Solar EPS) in improving short-term predictive stability for solar radiation in this region.
• Offers critical insights and recommendations for future model refinements, specifically highlighting the need for improved cloud–aerosol parameterizations to mitigate systematic errors.

Funding

Not provided in the given text.

Citation

@article{Zhang2025Assessment,
  author = {Zhang, Haoling and Li, Lei and Zhang, Xindan and Liu, Shuhui and Zheng, Yu and Gui, Ke and Ma, Jingrui and Che, Huizheng},
  title = {Assessment of WRF-Solar and WRF-Solar EPS Radiation Estimation in Asia Using the Geostationary Satellite Measurement},
  journal = {Remote Sensing},
  year = {2025},
  doi = {10.3390/rs17243970},
  url = {https://doi.org/10.3390/rs17243970}
}