作者: Jędrzej S. Bojanowski , Anton Vrieling , Andrew K. Skidmore
DOI: 10.1016/J.AGRFORMET.2013.03.005
关键词: Satellite 、 Multivariate interpolation 、 Radiation 、 Calibration 、 Mean squared error 、 Environmental science 、 Crop growth 、 Meteorology 、 Weather station 、 Remote sensing
摘要: Abstract Solar radiation is a key input variable for crop growth models. However, direct measurement of solar performed operationally only limited number weather stations. Instead measurements, empirical models are used that link to more commonly measured meteorological variables. Coefficients these site-dependent and therefore generally interpolated from the few locations where measured. In this study, three were calibrated (Angstrom–Prescott, Supit–Van Kappel, Hargreaves) using daily product derived Meteosat Second Generation data. This satellite-based calibration model coefficients led higher accuracy when estimating radiation, as compared use ground-based coefficients. The average relative root mean square error Generation-based was 1.9% lower Kappel (p