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Correction of parameters in Angstrom formula and analysis of total solar radiation characteristics in Huaibei plain |
YUAN Hongwei1,2, YUAN Xianjiang1,2, TANG Guangmin1,2, CUI Yi3, JIANG Shangming1,2 |
1.Water Resources Research Institute of Anhui Province, Bengbu, Anhui 233000, China; 2.Key Laboratory of Water Conservancy and Water Resources of Anhui Province, Bengbu, Anhui 233000, China; 2.State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin 300072, China |
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Abstract Based on the total solar radiation data observed by automatic meteorological equipment in the Xinmaqiao Experimental Station, Anhui province, during 2011—2016, the empirical coefficients a and b in the Angstrom formula were calibrated by least squares method and genetic algorithm. Additionally, ET0 and total solar radiation calculated by the calibrated values were compared with the recommended values by FAO. Based on the optimized empirical parameters and the data observed in five typical meteorological stations located in Dangshan, Bozhou, Suxian, Bengbu and Fuyang, the temporal and spatial distribution characteristics of the total solar radiation in the Huaibei plain were analyzed. The results show that the recommended values of a and b by FAO are unsuitable to the total solar radiation in the Huaibei plain because of overestimated Rs and ET0. The calibrated values by the least squares method and genetic algorithm can result in more accurate Rs and ET0. In 1955—2014, the average daily total solar radiation presents a downtrend from north to south in the plain, and the decline is larger in the north than in the south. The year of 1980 is a turning point before that adaily total solar radiation declined tendency is not obvious, but after that the radiation is declined obviously. The seasonal distribution characteristics of Rs from the largest to the smallest are: summer> spring> autumn>winter. The yearly and seasonally average Rs distributions are higher in the north and lower in the south generally, but there is a difference in Rs locally. Besides, the monthly Rs shows a unimodal distribution, its maximum is in June and the minimum is in December. These results can provide a reference for accurately calculating Rs and ET0 based on conventional meteorological data in the plain.
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Received: 24 April 2018
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