Elsevier

Energy

Volume 82, 15 March 2015, Pages 589-600
Energy

Changes in the relationship between solar radiation and sunshine duration in large cities of China

https://doi.org/10.1016/j.energy.2015.01.068Get rights and content

Highlights

  • Relationship between radiation and sunshine duration changed in large cities of China.

  • This change is due to aerosol pollutions under “dimming” and “brightening” context.

  • 10 years is recommended as the national standard for Angstrom calibration in China.

Abstract

Based on the linear relationship between solar radiation and sunshine duration, the Angstrom model is widely used to estimate solar radiation from routinely observed meteorological variables for energy exploitation. However, the relationship may have changed in quickly developing regions in the recent decades under global “dimming” and “brightening” context, with increasing aerosols due to industrial pollutions. Solar radiation stations under different climate conditions in six large cities in China are selected to test this hypothesis. Analysis of the related meteorological items shows that Guiyang has the lowest solar radiation with the average annual value of 10.5 MJm−2d−1, while Lhasa on the Tibetan Plateau has the highest of 20.1 MJm−2d−1. Both radiation and sunshine hours decreased from 1961 to 2010, but at different rates. A moving linear regression method is used to investigate the changes in the relationship between radiation and sunshine duration, the results indicate an abrupt change in the correlation coefficients in 1980–1990s, which can be attributed to the aerosol load resulting from air pollution caused by the industrial development in 1980s under China's Open Door Policy. The sky condition has been changing from clean to dirty, thus the relationship between solar radiation and duration changes in the 1980's and has recovered in the recent decades. This finding implies that it might not necessarily be right to use long data sets for model calibration. Further investigation confirms that the Angstrom model performs the best with higher NSE (nash-sutcliffe efficiency) of 0.914 and lower MAPE (mean absolute percentage error) and RMSE (root mean square error) values of 13.7 w/m2 and 23.9 w/m2 respectively, when calibrated with a 10-year data set. In contrast, the model performs worst when it is calibrated with a 40-year data set, with NSE, MAPE and RMSE values of 0.891, 15.1 w/m2 and 25.3 w/m2, respectively. Based on the findings of this research, a 10-year data set is recommended as the national standard for model calibration in rapidly developing regions of China. Further analogous investigations are needed in other industrial regions to make an international standard for Angstrom model calibration.

Introduction

Compared to the energy from fossil fuels, solar energy is believed to be even more important as clean energy not contributing to global warming [1]. Accurate identification of the temporal and spatial distribution of solar radiation is the essential premise to solar energy exploitation. However, solar radiation is not a routinely observed meteorological item as temperature or rainfall due to the high cost of instruments and maintenance. Up to now, solar radiation is only observed at very few particular stations in the developing nations, which means that the estimation of solar radiation is of vital importance for scientists in the domain of energy, meteorology, and agronomy, among others e.g. Refs. [2], [3], [4], [5].

Robust numerical models have already been established by meteorologists, but the requirement of too many input parameters makes this kind of model suitable only for theoretical analysis rather than practical applications [6], [7]. In contrast, simple empirical models are still the main tool for solar radiation estimation [8]. Based on the relationship between solar radiation and readily available meteorological parameters, such as sunshine duration, temperature, rainfall etc., different kind of simple empirical models have been developed [9], [10], [11], [12]. Comparison of different kinds of empirical models identified that the sunshine-based model performed better than the temperature- and rainfall-based ones [4], [13], [14], [15], even under the unique alpine conditions [16], and the sunshine-based Angstrom model is likely the most popular empirical model for solar radiation estimations [13], [17], [18], [19], [20], [21]. Since the coefficients of the Angstrom model are site-specific, the first step for the model application is to calibrate the model with the collected radiation and sunshine data set. However, the length of the data set used for the calibration seems casual. Different lengths of the data set have been used for model calibration, varying from 1 year [4], 5 years [13], 10 years [20] to 40 year or so [22]. There seems an intuitive tendency that the calibration should be made with data set as long as possible, if only the related data set can be obtained [23]. Of course, in the view of statistics, longer data sets for model calibration always means more reliable parameters [24], under assumption that the relationship between solar radiation and sunshine duration is stationary.

However, there is increasing evidence that the amount of solar radiation incident at the earth's surface is not stable over the years but undergoes significant decadal variations [25], which is referred to as “global dimming” and “brightening” [26]. As for the quickly developing regions like China, Qian et al. [27] suggested that the increasing aerosol loading from emissions of pollutants is responsible for the observed reduced global radiation. It was identified that both radiation and sunshine duration have decreased in the recent decades, partly or entirely due to changes in aerosol concentrations under global “dimming” and “brightening” context [25], [26], [27], [28]. If the changing trend of radiation and sunshine duration were not synchronized, we can cautiously envisage that the relationship between solar radiation and sunshine duration may have changed. But up to now, no research to our knowledge has been conducted to test this hypothesis.

With the Open Door Policy in the 1980s, China developed quickly with significant environmental issues, especially air pollution due to increasing aerosols [27]. In this research, solar radiation and sunshine duration data were collected at radiation stations in six large cities of China under different climate conditions. The objectives of the study are: (1) to test the hypothesis that the relationship between radiation and sunshine duration has changed in the large cities of China, under “global dimming and brightening” context; (2) to address a corresponding strategy for solar radiation estimation, if the hypothesis can be validated; and (3) to give the scientific basis for a national standard of solar radiation estimation.

Section snippets

Database

For this research, access to the database of the NMIC (national meteorological information center) was given by the CMA (China meteorological administration). Study of the influence of different time scales on the Angstrom calibration indicated that calibration made on daily basis has important advantages on monthly scale with stabilized coefficients and more accurate prediction [22], therefore daily solar radiation and the related meteorological parameters, including sunshine duration, cloud

Statistical analysis of solar radiation and related meteorological items

Long-term variations of solar radiation and sunshine duration are shown in Fig. 2. Lhasa on the Tibetan plateau has the highest average annual solar radiation of 20.1 MJm−2d−1, which can be attributed to its high altitude (3650.1 m a.s.l.). In contrast, Guiyang has the lowest solar radiation with the average annual value of 10.1 MJm−2d−1, nearly half of that in Lhasa, which can be attributed to its high cloud coverage and excessive rainy days. The highest sunshine duration is also found in

Discussion

Previous research has focused on the trend analysis of solar radiation and sunshine duration by the linear regression method, [32], [33], [34], [35]. However, the simple linear regression cannot reveal the characteristics of the relationship between radiation and sunshine duration, which is the essential scientific basis for solar radiation estimation with the Angstrom model. In this research, the moving linear regression method was used and successfully depicted the variation processes of the

Summary and conclusions

Solar radiations under different climate conditions in six large cities in China were selected to detect the changes in the relationship between solar radiation and sunshine duration in recent decades. Analysis of solar radiation and its related meteorological variables indicated that Lhasa has the highest solar radiation with average annual value of 20.1 MJm−2d−1, while Guiyang the lowest of 10.5 MJm−2d−1. Both solar radiation and sunshine duration have decreased in the recent decades, but at

Acknowledgment

This research is jointly supported by the National Science Foundation of China (No. 41105079) and Special Key Project on “Estimation and Prediction of the Solar Radiation in China” (No. GYHY201306048). The authors sincerely thank the anonymous referees for their strict but instructive comments on the manuscript. Special thanks are also extended to the weathermen at Lhasa station on the Tibetan Plateau under altitude hypoxia conditions.

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