A method for daily global solar radiation estimation from two instantaneous values using MODIS atmospheric products. (15th September 2016)

• Record Type: Journal Article
• Authors: Xu, Xiaojun; Du, Huaqiang; Zhou, Guomo; Mao, Fangjie; Li, Pingheng; Fan, Weiliang; Zhu, Dien
• Is Part Of: Energy. Volume 111(2016)
• Page Start: 117
• Page End: 125
• Publication Date: 2016-09-15
• Subjects: Daily global solar radiation -- MODIS -- Total cloud fraction -- MERRA; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2016.05.095
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: Accurate information on the temporal and spatial distributions of solar radiation is very important in many scientific fields. In this study, instantaneous solar irradiances on a horizontal surface at 10:30 and 13:30 local time (LT) were calculated from Moderate Resolution Imaging Spectroradiometer (MODIS) atmospheric data products with relatively high spatial resolution using a solar radiation model. These solar irradiances were combined to derive half-hourly averages of solar irradiance (HASI) and daily global solar radiation (GSR) on a horizontal surface using linear interpolation, piecewise linear regression, and quadratic polynomial regression. Compared with field observations, the HASI were estimated accurately when the total cloud fraction (TCF) was <0.6. The accuracy of the estimates of the HASI was determined mainly by the quality of TCF. For TCF values <0.6, linear interpolation performed best, whereas quadratic polynomial regression was superior to the other methods for TCF values >0.6. Overall, the daily GSR estimated in this study was better than that estimated by the Modern-Era Retrospective Analysis for Research and Applications (MERRA) reanalysis of NASA. The daily GSR estimated in this study was underestimated, whereas it was overestimated by MERRA. The combination of the daily GSR estimates of this study and MERRA offers a simple and feasible technique for reducing uncertainty in daily GSR estimates. Highlights: Daily GSR is integrated from two observations from the MODIS products. Daily GSR from the MODIS products is underestimated. Biases were attributed primarily to variations in the total cloud percent. Combining daily GSR estimates from the MODIS and the MERRA increases accuracy.