کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8073192 | 1521437 | 2016 | 9 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A method for daily global solar radiation estimation from two instantaneous values using MODIS atmospheric products
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی انرژی
انرژی (عمومی)
پیش نمایش صفحه اول مقاله

چکیده انگلیسی
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.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Energy - Volume 111, 15 September 2016, Pages 117-125
Journal: Energy - Volume 111, 15 September 2016, Pages 117-125
نویسندگان
Xiaojun Xu, Huaqiang Du, Guomo Zhou, Fangjie Mao, Pingheng Li, Weiliang Fan, Dien Zhu,