Assessment of WRF-Solar and WRF-Solar EPS Radiation Estimation in Asia Using the Geostationary Satellite Measurement

Abstract

What are the main findings?

The WRF-Solar EPS model shows comparable short-term (<36 h) forecasting capabilities to WRF-Solar, the model performing well in the Beijing-Tianjin-Hebei region and the Yangtze River Delta. Bias is lower in summer and autumn, while RMSE and MAE are lower in autumn and winter.

There is a temporal mismatch in the seasonal fluctuations of the bias, root mean square error, and mean absolute error of GHI. The errors fluctuations in DIR over Western China follow a distinctive pattern.

What are the implications of the main findings?

Ensemble forecasting can slightly enhance the stability of forecast results, but improve results little in short-term forecasting.

The error performance of WRF-Solar and WRF-Solar EPS in the short-term prediction of solar irradiance at the interannual scale in Asia is quantitatively evaluated, which provides a basic reference for subsequent improvement work.

Accurate solar radiation forecasting with numerical weather prediction (NWP) is critical for optimizing photovoltaic power generation. This study evaluates short-term (<36 h) 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 (December 2019–November 2020) against geostationary satellite retrievals. Both models effectively capture GHI spatial patterns but exhibit systematic overestimation (biases: 17.27–17.68 W/m²), with peak errors in northwest China and the North China Plain. Temporal mismatches between bias (maximum in winter-spring) and RMSE/MAE (maximum in summer) may indicate seasonal variability in error signatures dominated by aerosols and clouds. For DIR, regional biases prevail: overestimation in the Tibetan Plateau and northwest China, and underestimation in southern China and Indo-China Peninsula. Errors (RMSE and MAE) are larger than for GHI, with peaks in southeast and northwest China, likely linked to poor cloud–aerosol simulations. WRF-Solar EPS shows no significant bias reduction but modest RMSE/MAE improvements in summer–autumn, particularly in southeast China, indicating limited enhancement of short-term predictive stability. Both WRF-Solar and WRF-Solar EPS require further refinements in cloud–aerosol parameterizations to mitigate systematic errors over East Asia in future applications.