Evaluation of numerical weather prediction for intra-day solar forecasting in the continental United States

Abstract

Numerical weather prediction (NWP) is generally the most accurate tool for forecasting solar irradiation several hours in advance. This study validates the North American Model (NAM), Global Forecast System (GFS), and European Centre for Medium-Range Weather Forecasts (ECMWF) global horizontal irradiance (GHI) forecasts for the continental United States (CONUS) using SURFRAD ground measurement data. Persistence and clear sky forecasts are also evaluated. For measured clear conditions all NWP models are biased by less than 50 W m −2. For measured cloudy conditions these biases can exceed 200 W m −2 near solar noon. In general, the NWP models (especially GFS and NAM) are biased towards forecasting clear conditions resulting in large, positive biases. Mean bias errors (MBE) are obtained for each NWP model as a function of solar zenith angle and forecast clear sky index, kt ∗, to derive a bias correction function through model output statistics (MOS). For forecast clear sky conditions, the NAM and GFS are found to be positively biased by up to 150 W m −2, while ECMWF MBE is small. The GFS and NAM forecasts were found to exceed clear sky irradiances by up to 40%, indicating an inaccurate clear sky model. For forecast cloudy conditions ( kt ∗ < 0.4) the NAM and GFS models have a negative bias of up to −150 W m −2. ECMWF forecasts are most biased for moderate cloudy conditions (0.4 < kt ∗ < 0.9) with an average over-prediction of 100 W m −2. MOS-corrected NWP forecasts based on solar zenith angle and kt ∗ provide an important baseline accuracy to evaluate other forecasting techniques. MOS minimizes MBE for all NWP models. Root mean square errors for hourly-averaged daytime irradiances are also reduced by 50 W m −2, especially for intermediate clear sky indices. The MOS-corrected GFS provides the best solar forecasts for the CONUS with an RMSE of about 85 W m −2, followed by ECMWF and NAM. ECMWF is the most accurate forecast in cloudy conditions, while GFS has the best clear sky accuracy.