Large forecast errors (forecast busts) for surface solar radiation (SSR) and therefore photovoltaic power generation may lead to either a shortage of power supply or production of excessive surplus power. Ensemble forecasting with numerical weather prediction (NWP) models has been developed to reduce forecast errors by taking the average of individual forecasts and to consider forecast uncertainty and reliability by generating a probabilistic forecast of meteorological fields. A multi-center grand ensemble (MCGE) is recognized as a useful technique for further reducing the uncertainty of a weather forecast. An ensemble mean of MCGE (EMg) has smaller forecast error than an ensemble mean of a single NWP center (EM). Moreover, the lognormal ensemble spread of MCGE (LNES8) and single-NWP-center ensembles (LNES) relate to the forecast error, and can be used as a predictor of reliability for the weather forecast. 1- to 6-day ensemble forecasts at four leading NWP centers (European Centre for Medium-Range Weather Forecasts: ECMWF, Japan Meteorological Agency: JMA, National Centers for Environmental Prediction: NCEP, and the UK Met Office: UKMO) were used to detect the forecast busts of daily SSR over the Kanto Plain in central Japan in a day-ahead regional forecast operated by the Japan Meteorological Agency (JMA-MSM). The magnitude of the forecast error of the EM, was found to be comparable with that of the JMA-MSM. The correlations between the forecast error coefficient (Fc) and LNESg in winter season were higher than summer season. In the top 10%, 5% and 1% forecast busts in five winter months, the Receiver Operating Characteristic (ROC) scores of the MCGE in 1- to 6-day ahead forecast indicated statistical significance. The LNES8 can therefore be a valuable predictor for detection of forecast busts in the regional forecast.