title: [Improving accumulation-mode fraction based on spectral aerosol optical depth in Beijing].
abstract: In the present study, the authors put forward a parameterization method of correcting fine-mode Angstrom index with aerosol optical depth and volume distribution of aerosol derived from AERONET in Beijing over 2011. The parameterization method is coupled with aerosol optical depth spectral deconvolution algorithm to improve the accuracy of accumulation-mode fraction. The errors of estimated AMF are derived from underestimate of fine-mode Angstrom index errors. We calculate and simulate the extreme values of fine-mode Angstrom index, getting constraint conditions, and then establish the extreme values correction method. Results from sensitivity test suggest that extreme values of fine-mode Angstrom index are constrained in the reasonable range. Finemode Angstrom index and AMF are sensitive to normalized volume distribution of aerosol, ranging from 0.662 to 2.849 and from 0.08 to 0.84 due to different distribution. Mean deviation of accumulation-mode fraction is reduced from 0.072 to 0.044, and the difference is 38.89%, especially in winter and summer. Improving computational accuracy of accumulation-mode fraction can enhance that of anthropogenic aerosol optical thickness, and it has important significance of anthropogenic aerosol direct radiation force estimation and environmental quality assessment.
authors.affiliation: Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China. zhang_ying1983@hotmail.com
authors.forename: Ying
authors.initials: Y
authors.lastname: Zhang
authors.affiliation: Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China.
authors.forename: Zheng-Qiang
authors.initials: ZQ
authors.lastname: Li
authors.affiliation: Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China.
authors.forename: Yan
authors.initials: Y
authors.lastname: Wang
authors.affiliation: Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China.
authors.forename: Kai-Tao
authors.initials: KT
authors.lastname: Li
authors.affiliation: Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China.
authors.forename: Dong-Hui
authors.initials: DH
authors.lastname: Li
authors.affiliation: Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China.
authors.forename: Yu-Huan
authors.initials: YH
authors.lastname: Zhang
authors.affiliation: Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China.
authors.forename: Peng
authors.initials: P
authors.lastname: Wei
authors.affiliation: Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China.
authors.forename: Ling
authors.initials: L
authors.lastname: Wang
authors.affiliation: Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China.
authors.forename: Yang
authors.initials: Y
authors.lastname: Lü