Hybrid Analysis and Nowcasting of Surface Solar Radiation Components in the INCA Framework

Gridded short-wave surface radiation components are essential for meteorology, hydrology, and renewable energy forecasting. In particular, solar power prediction for photovoltaic (PV) and concentrated solar power (CSP) systems depends critically on accurate short-range forecasts of global, direct, and diffuse irradiance. Delivering such high-resolution, site-specific estimates is a core objective of the FFG-funded PV4Community project and the focus of the presented work. 

A hybrid analysis–nowcasting approach has been implemented in the INCA (Integrated Nowcasting through Comprehensive Analysis; Haiden et al. 2011) radiation module. It combines global irradiance and sunshine duration observations from the Austrian monitoring network, MTG satellite retrievals, and high-resolution NWP guidance from AROME and C-LAEF. Strong coupling to INCA’s cloud analysis and cloud-motion nowcasting enables high spatial detail and very short-range accuracy, while accounting for low-sun-angle conditions and the effects of Alpine topography (terrain shading, slope, aspect). 

Radiation fields are produced on a 1 km × 1 km grid at 15-minute frequency with lead times up to 48 h. A key advancement is the derivation of diffuse and direct radiation components using an adapted version of the Gassel (1999) algorithm. The original Gassel method describes a physically consistent partitioning of global horizontal irradiance into its beam and diffuse components based on solar geometry and atmospheric transmissivity. Our adaptation extends this approach for operational nowcasting by: (i) dynamically coupling the algorithm with INCA’s global irradiance output, (ii) incorporating MTG-based cloud physical properties, and (iii) adjusting the clear-sky and turbidity assumptions to the Alpine environment. This yields a robust irradiance decomposition that remains stable across rapidly changing cloud scenes and complex terrain. 

Validation against measurements from the ARAD radiation network (Olefs et al. 2016) demonstrates high correlation and low bias for both diffuse and direct irradiance, confirming the suitability of the new components for operational solar energy applications. Their integration into the INCA framework ensures sustained, near-real-time availability and opens the door for improved PV nowcasting, solar ramp detection, and future energy system applications. 

Funding: This work was supported by the Austrian Research Promotion Agency (FFG; www.ffg.at). 

 

Haiden, T., Kann, A., Wittmann, C., Pistotnik, G., Bica, B., & Gruber, C. (2011). The Integrated Nowcasting through Comprehensive Analysis (INCA) system and its validation over the Eastern Alpine region. Weather and Forecasting, 26(2), 166-183. 

Gassel, A. (1999). Beiträge zur Berechnung solarthermischer und exergieeffizienter Energiesysteme (Doctoral dissertation, Fraunhofer-IRB-Verlag). 

Olefs, M., Baumgartner, D. J., Obleitner, F., Bichler, C., Foelsche, U., Pietsch, H., ... & Schöner, W. (2016). The Austrian radiation monitoring network ARAD–best practice and added value. Atmospheric Measurement Techniques, 9(4), 1513-1531.