Abstract
WRF-Solar is a numerical weather prediction (NWP) model specifically designed to meet the increasing demand for accurate solar irradiance forecasting. The model provides flexibility in the representation of the aerosol-cloud-radiation processes. This flexibility can be argued to make more difficult to improve the model’s performance due to the necessity of inspecting different configurations. To alleviate this, WRF-Solar has a reference configuration to use it as a benchmark in sensitivity experiments. However, the scarcity of high-quality ground observations is a handicap to accurately quantify the model performance. An alternative to ground observations are satellite irradiance retrievals. Herein we analyze the adequacy of the National Solar Radiation Database (NSRDB) to validate the WRF-Solar performance using high-quality global horizontal irradiance (GHI) observations across the CONUS. Based on the sufficient performance of NSRDB, we further analyze the WRF-Solar forecast errors across the CONUS, the growth of the forecasting errors as a function of the lead time, sensitivities to the grid spacing, and to the representation of the radiative effects of unresolved clouds. Our results based on WRF-Solar forecasts spanning the year of 2018 reveal a 7% median degradation of the mean absolute error (MAE) from the first to the second daytime period. Reducing the grid spacing from 9 km to 3 km leads to a 4% improvement in the MAE, whereas activating the radiative effects of unresolved clouds is desirable over most of the CONUS even at 3 km of grid spacing. A systematic overestimation of the GHI is found. These results illustrate the potential of GHI retrievals to contribute increasing the WRF-Solar performance.
Energy and exergy analysis of air based photovoltaic thermal (PVT) collector: a review