Site-Dependent Evaluation of the ECMWF IFS-HRES and IFS-COMPO Intra- and Day-ahead Forecasts with Respect to Surface Solar Irradiances

Kurzfassung

The main focus of the CAMS Radiation Service (CRS) is to provide high-quality long-term historical irradiance data suited for various application of solar energy such as solar resource assessments, system monitoring and forecast. CRS is based on outputs of the CAMS atmospheric composition model which provides analysis, forecast and reanalysis of atmospheric composition, such as - among others - aerosols, water vapor and ozone (Inness et al., 2015). The CAMS atmospheric composition model also includes a surface radiation product which is referred to as IFS-COMPO in this work (Integrated Forecasting System, atmospheric composition). Another model -IFS-HRES (Integrated Forecasting System, High Resolution)- is operated by the European Center for Medium Range forecast (ECMWF) with a focus on meteorological forecasts. Due to operational constraints, IFS-HRES is not coupled with the atmospheric content of CAMS but rely on an aerosol climatology (Bozzo et al., 2017). The IFS-COMPO forecast is operated on a spatial resolution of 40 km (~ 0.4°) which is quite coarse compared to the 9 km (~0.1°) of the operational IFS-HRES. With a better consideration of the atmospheric content, we can expect that the performance of IFS-COMPO is better than IF-HRES in cloud free conditions. However, the better resolution of IFS-HRES may counterbalance the benefits of detailed information of the atmospheric content. A comparison of IFS-COMPO and IF-HRES is therefore interesting to understand the relative importance of a detailed consideration of the atmospheric content and the model resolution for estimating the surface solar irradiance (SSI). The objective of this work is to understand how the IFS-COMPO radiation forecast compares to the operational IFS-HRES forecast and whether the IFS-COMPO forecast fits better for some specific solar energy applications. The present evaluation is done for the full year 2022 on a global scale using ground observations from well-known research solar radiation measurement networks (BSRN, SAURAN, SURFRAD, enerMENA, NREL-MIDC). In a first step, all ground observations are passed through the expert QC battery of tests developed by the CAMS radiation service team. Then, the locations of these observations are classified into 5 types: desert, polar, sub-pixel, mountainous, and continental. This classification scheme allows to identify strengths and weaknesses and to compare the performances of the forecasts from different perspectives.