Royal Dutch Meteorological Institute; Ministery Of Infrastructure And The Environment

Publications, presentations and other activities
Surface solar radiation forecasts by advecting cloud physical properties derived from Meteosat Second Generation observations.
2018
by P. Wang (KNMI), R.M. van Westrhenen (KNMI), J.F. Meirink (KNMI), S.H. van der Veen (KNMI), W.H. Knap (KNMI)

A surface solar radiation forecast algorithm is developed using cloud physical properties from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on board of the Meteosat Second Generation (MSG) geostationary satellite. The novelty of the algorithm is the derivation of cloud motion vectors using cloud physical properties. The solar radiation forecast products include global horizontal irradiance (GHI) and direct normal irradiance (DNI). The forecast horizon is 04 h at a 15 min temporal resolution. The forecast is currently tested for the Netherlands at a spatial resolution of about 4 km  6 km. Compared to measurements of the Baseline Surface Radiation Network (BSRN) site of Cabauw, the root mean square error (RMSE) is about 3144% for GHI and 59100% for DNI at a forecast horizon of 2 h. For a forecast horizon of 15 min, the RMSE is 2224% for GHI and 4361% for DNI. The correlation coefficients between the forecasts and BSRN measurements are similar for GHI and DNI, and decrease from about 0.80.9 at 15 min to 0.450.75 at 2 h. The SEVIRI forecast outperforms the HARMONIE numerical weather prediction model forecast in the first 23 h. The quality of the forecast depends on the sky conditions: for clear-sky indices larger than 0.7, the SEVIRI GHI forecast is better than both smart persistence and the HARMONIE forecast in the first 4 h.

Bibliographic data
Wang, P., R.M. van Westrhenen, J.F. Meirink, S.H. van der Veen and W.H. Knap, Surface solar radiation forecasts by advecting cloud physical properties derived from Meteosat Second Generation observations.
Solar Energy, 2018, 177, 47-58, doi:https://doi.org/10.1016/j.solener.2018.10.073.
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