Solar radiation is a key input variable for crop growth models. However, direct measurement of solar radiation is performed operationally for only a limited number of weather stations. Instead of direct measurements, empirical solar radiation models are used that link solar radiation to more commonly measured meteorological variables. Coefficients for these models are site-dependent and therefore generally interpolated from the few locations where solar radiation is measured. In this study, three solar radiation models were calibrated (Ångström-Prescott, Supit-Van Kappel, and Hargreaves) using a daily solar radiation product derived from Meteosat Second Generation data. This satellite-based calibration of model coefficients led to a higher accuracy when estimating daily solar radiation, as compared to the use of interpolated ground-based model coefficients. The average relative root mean square error for Meteosat Second Generation-based calibrated models was 1.9% lower for the Supit-Van Kappel model (p<0.001, n=137), and 1.8% lower for the Hargreaves model (p<0.001, n=222). There was no significant improvement using the Ångström-Prescott model. The Meteosat Second Generation-based model coefficients were interpolated to create continuous coefficient maps for Europe. From these maps it is possible to estimate solar radiation from the sunshine duration, cloud coverage and air temperature range for every location in Europe without prior calibration. We conclude that Meteosat Second Generation-based calibration of model coefficients improves the accuracy of solar radiation estimates.
- Solar radiation
- Model calibration
- MARS Crop Yield Forecasting System
- Remote sensing
- Spatial interpolation