Solar Calc: Estimating Hourly Incoming Solar Radiation from Limited Meteorological Data Two major properties which 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, a majority of 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 (mm) with daily minimum and maximum air temperatures (degrees C). The file format for this weather data file is a comma spaced value file (CSV) with the following format: DOY, MIN, MAX, PREC Where DOY is day of year, MIN is the minimum air temperature, MAX is the maximum air temperature, and PREC is the total daily rainfall. Each day has a separate line in the file. 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, d-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. Disclaimer: The USDA-ARS makes no warranties as to the merchantability or fitness of SolarCalc 1.0 for any particular purpose, or any other warranties expressed or implied. Since some portions of SolarCalc 1.0 have been validated with only limited data sets, it should not be used to make operational management decisions. The USDA-ARS is not liable for any damages resulting from the use or misuse of SolarCalc 1.0, its output and its accompanying documentation. SolarCalc 1.0 was written in Java, and therefore can run on multiple platforms (e.g. Windows, Mac, Unix).