Effect of Time of Temperature Observation and Estimation of Daily Solar Radiation for the Northern Great Plains, USA

Abstract

Daily incident solar radiation is an important input for numerous crop growth simulation models. However, lack of recorded solar radiation is a significant impediment for most crop–climate studies. The present study aimed to overcome the problem of sparse historical data of solar radiation over the northern Great Plains. The approach was to develop a physically based solar radiation model wherein estimates were possible with minimum input data. In addition, this study investigates impacts of time of observation bias on the model formulation. The proposed model (M‐H) requires measured daily range of air temperature (maximum minus minimum) and estimated daily clear‐sky solar radiation. Daily weather data (including solar radiation measurements) for nine stations with observations from 1990 through 1998 were used for formulation of the final model. To determine potential bias associated with the reporting time, three times—0800, 1600, and 2400 h—were tested. Based on superior performance, the solar radiation model formulated with 2400‐h reporting time data from Akron, CO, was selected for the whole region. The model underestimated high values. Local‐scale advection and frontal passage were apparently responsible for this bias. This proposed model was also compared with two forms of the Bristow–Campbell (B‐C) model. Both of these forms show significant improvement for 2400‐h observation time. One particular form of the B‐C model performs slightly better than the model proposed here. However, it also underestimates high values like the M‐H model and shows slight regional bias. This study finds that, overall, the M‐H model is more stable than the B‐C model.