Estimating hourly incoming solar radiation from limited meteorological data

Abstract

Two major properties that determine weed seed germination are soil temperature and moisture content. Incident radiation is the primary variable controlling energy input to the soil system and thereby influences both moisture and temperature profiles. However, many agricultural field sites lack proper instrumentation to measure solar radiation directly. To overcome this shortcoming, an empirical model was developed to estimate total incident solar radiation (beam and diffuse) with hourly time steps. Input parameters for the model are latitude, longitude, and elevation of the field site, along with daily precipitation with daily minimum and maximum air temperatures. Field validation of this model was conducted at a total of 18 sites, where sufficient meteorological data were available for validation, allowing a total of 42 individual yearly comparisons. The model performed well, with an average Pearson correlation of 0.92, modeling index of 0.95, modeling efficiency of 0.80, root mean square error of 111 W m−2, and a mean absolute error of 56 W m−2. These results compare favorably to other developed empirical solar radiation models but with the advantage of predicting hourly solar radiation for the entire year based on limited climatic data and no site-specific calibration requirement. This solar radiation prediction tool can be integrated into dormancy, germination, and growth models to improve microclimate-based simulation of development of weeds and other plants.