Correcting solar radiation from reanalysis and analysis datasets with systematic and seasonal variations

Abstract

Global Horizontal Irradiance (GHI), a component of solar radiation, is used to assess potential and estimate power output of solar thermal and PV applications. The reanalysis or analysis data are alternative to satellite data for solar resource assessment in places where latter is not available or costly, so there is need to evaluate their performance. The evaluation of estimated GHI (six-hourly data) from five global reanalysis and analysis datasets (NCEP-NCAR, NCEP-DOE, CFSR, NCEP-GFS and NCEP-FNL) is performed using annual, seasonal and monthly statistical analyses. The range of annual rMBE, rMAE, rRMSE and R is 13–41%, 23–41%, 44–66% and 0.938–0.965 respectively in the two inspected stations for all reanalysis and analysis datasets. Systematic errors were observed in estimated GHI which signifies need to apply bias correction to get data with acceptable uncertainty. Five bias correction methods based on Measure-Correlate-Predict, Linear-Adaptation (LA1 and LA2), CDF and Model Output Statistics (MOS) were applied to correct original GHI. The range of rMAE and rRMSE after bias-correction is 12–19% and 23–37% respectively for six-hourly data. The overall results of MOS method are best, followed by the linear-adaptation method. The corrected GHI from CFSR and NCEP-GFS datasets can be used for preliminary solar resource assessment.