Evaluation of a technique to estimate solar radiation in the southeastern United States for use in agricultural models

Solar radiation is an essential atmospheric measurement for agricultural practices with direct impacts to plant monitoring and modeling, irrigation applications, and integrated pest management.

Crop models such as those included in the Decision Support System for Agrotechnology Transfer (DSSAT) have been developed to predict crop growth patterns. These models require accurate local climate information including air temperature, precipitation, and incoming radiation. However, solar radiation observations are only available for a limited number of locations across the United States. In the absence of observations, an estimation of incoming radiation is usually required.

This study evaluates the accuracy of solar radiation estimation techniques based on Hargreaves (1982), Bristow and Campbell (1984), and Thornton and Running (1999) as compared to observations from sensors in the southeastern United States. Spatial and temporal patterns are analyzed with an emphasis during the growing season period of May through September. Since radiation observations suggest high spatial variability, these techniques are analyzed for accuracy both at regional and local scales. In addition, this study evaluates a modification to Hargreaves (1982) technique that estimates potential cloud cover based on observed precipitation.