Assessment of Medium-Range and Sub-Seasonal Ensemble Forecasts of Solar Irradiance and Wind Speed Over China: Applications for Renewable Energy

Renewable energy development in China relies heavily on accurate forecasts of surface solar irradiance and 10-meter wind speed. This study evaluates the medium-range and sub-seasonal forecast performance of the European Centre for Medium-Range Weather Forecasts operational ensemble (ECMWF-ENS) over China. Forecast data, provided at a 6-hour time step, are assessed against gridded observational datasets from the China Meteorological Administration (CMA). Using metrics such as mean absolute error, root mean square error, and mean bias error, the study examines the forecast accuracy across different seasons and regions in China. Results reveal that the ensemble forecasts effectively capture diurnal cycles and regional variability in solar irradiation and wind speed. However, forecast errors vary significantly based on the climate variable and time of year, with solar irradiation forecasts generally demonstrating higher accuracy during summer months. The study highlights the role of the atmosphere in modulating solar and wind energy potential, emphasizing the critical need for accurate, high-resolution forecasts to support renewable energy applications. The findings demonstrate that spatially continuous hourly predictions can reconstruct regional-scale variations, providing valuable insights for optimizing site selection for solar and wind power plants. This research underscores the importance of reliable medium-range and sub-seasonal forecasting systems for advancing renewable energy planning and addressing China's growing energy demands while supporting climate adaptation strategies.