J. Kim, RAL/NCAR

WRF-Solar Ensemble Prediction System (WRF-Solar EPS) has been developed by introducing stochastic perturbations in the most relevant physical variables for solar irradiance predictions. In this study, we comprehensively discuss the impact of the stochastic perturbations of WRF-Solar EPS on solar irradiance forecasting compared to deterministic WRF-Solar predictions, a stochastic ensemble using the stochastic kinetic energy backscatter scheme (SKEBS), and a WRF-Solar multi-physics ensemble (WRF-Solar PHYS). The performances of the four forecasts are evaluated using irradiance retrievals from the National Solar Radiation Database (NSRDB) over the contiguous U.S. We focus on the performance of the day-ahead solar irradiance predictions during the year of 2018. The results show that the ensemble forecasts improve the quality of the forecasts compared to the deterministic prediction system by taking into account the uncertainty derived by the ensemble members. However, the three ensemble systems are under-dispersive, producing unreliable and overconfident forecasts due to the lack of calibration. In particular, WRF-Solar EPS produces less optically thick clouds than the other forecasts, which explains a larger positive bias in WRF-Solar EPS (31.7 W/m2) than in the other models (22.7-23.6 W/m2). The results provide guidelines for improving the performance of WRF-Solar EPS in the future.