Calibration and Validation of the Angstrom-Prescott Model in Solar
Radiation Estimation using Optimization Algorithms
Abstract
The Angstrom-Prescott (A-P) model is widely suggested for estimating
solar radiation (Rs) in areas without measured or
deficiency of data. The coefficients of this model must be locally
calibrated, to calculate evapotranspiration (ET) correctly. The aim of
this research was calibration and validation of the coefficients of the
A-P model at six meteorological stations across arid and semi-arid
regions of Iran. This model was improved by adding the air temperature
and relative humidity terms. Besides, the coefficients (’a’ and ‘b’) of
the A-P model and improved models was calibrated using some optimization
algorithms including Harmony Search (HS) and Shuffled Complex Evolution
(SCE). Performance indices, i.e., Root Mean Square Error (RMSE), Mean
Bias Error (MBE), and coefficient of determination
(R2) were used to analyze the models ability in
estimating Rs. The results indicated that the
performance of the A-P model had more precision and less error than
improved models in all the stations. In addition, the best results were
obtained for the A-P model with the SCE algorithm. The RMSE varies
between 0.82 and 2.67 MJ m-2 day-1
for the A-P model with the SCE algorithm in the calibration phase. In
the SCE algorithm, the values of RMSE had decreased about 4% and 7%
for Mashhad and Kerman stations in the calibration phase compared to the
HS algorithm, respectively. In other words, the highest decrease of RMSE
is related to Kerman station.