Abstract: In this study, the determination of the Angstrom coefficients of a, and b was conducted with the measured global solar radiation datasets from the stations of Jinan, Yantai, and Juxian. Then, the Angstrom formula was used to estimate global solar radiation based on daily sunshine duration data at 17 meteorological stations in Shandong Province during the period 1961- 2012. The spatial distribution of annual and seasonal total global solar radiation was derived with the spatial interpolation method. The temporal trend and abrupt change of annual and seasonal total global solar radiation were detected with the methods of linear regression and Pettitt test, respectively. The results show that the annual global solar radiation averaged over 1961- 2012 were ranged from 4814.3-5338.8 MJ/m². The spatial distribution of mean annual global solar radiation over 1961-2012 was generally high in the north, but low in the south of Shandong Province. The time series of annual and summer season global solar radiation showed decreasing trends during the past 52 years. Except for Weihai station, all other stations exhibited significant decreasing trend at least 95% confidence level. Significant decreasing trends were detected at most stations in summer and winter, whereas only 3 and 1 stations showed increasing trend in spring and autumn, respectively. Significant trends were observed at 23.5%, 64.7% and 76.5% stations in spring, autumn, and winter, respectively. The stations located in the middle and southwest of Shandong Province were exhibited more faster decreasing rate compared with the other stations located in the north and peninsula of Shandong Province. During the past 52 years, a period with high value of annual global solar radiation and a period with low value were detected. Significant downward shift in the annual time series of global solar radiation was detected at all of the 17 meteorological stations. Significant downward shifts were detected at 6, 15, 14 and 11 stations in the spring, summer, autumn and winter time series.