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Andrew R. Jongeward, Zhanqing Li, Hao He, and Xiaoxiong Xiong

through December 2012 covering data from MODIS Aqua and January 2001 through December 2009 covering data from the high-resolution GOCART aerosol model. Each of the datasets passes through a three-step analysis consisting of 1) deseasonalization, 2) linear regression, and 3) application of significance testing (the Student’s t test). The goal is to analyze the interannual behavior of any observed trends, and, as such, the mean seasonal climatology is first removed (i.e., deseasonalized) following

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Daniel Rothenberg and Chien Wang

.-K. , J.-P. Chen , Z. Li , C. Wang , and C. Zhang , 2011 : Impact of aerosols on convective clouds and precipitation . Rev. Geophys. , 50 , RG2001 , doi: 10.1029/2011RG000369 . Tatang , M. A. , W. Pan , R. G. Prinn , and G. J. McRae , 1997 : An efficient method for parametric uncertainty analysis of numerical geophysical models . J. Geophys. Res. , 102 , 21 925 – 21 932 , doi: 10.1029/97JD01654 . Tibshirani , R. , 2011 : Regression shrinkage and selection via the

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Tianmeng Chen, Jianping Guo, Zhanqing Li, Chuanfeng Zhao, Huan Liu, Maureen Cribb, Fu Wang, and Jing He

(including all cases with visibilities greater than 30 km) is excluded from the analysis in this study. Visibility measurements suffer not only from major limitations such as high uncertainty due to the nature of human observation but also from the impact of relative humidity (RH). Hygroscopic growth of aerosol particles in a high RH environment may lead to decreases in visibility measurements and underestimate the corresponding aerosol loading ( Cheng and Tsai 2000 ; Che et al. 2007 ; Guo et al. 2009

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