Optimal Estimation Retrieval of Aerosol Fine-Mode Fraction from Ground-Based Sky Light Measurements
Fengxun Zheng,
Weizhen Hou,
Xiaobing Sun,
Zhengqiang Li,
Jin Hong,
Yan Ma,
Li Li,
Kaitao Li,
Yizhe Fan,
Yanli Qiao
Affiliations
Fengxun Zheng
State Environment Protection Key Laboratory of Satellite Remote Sensing, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China
Weizhen Hou
State Environment Protection Key Laboratory of Satellite Remote Sensing, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China
Xiaobing Sun
Key Laboratory of Optical Calibration and Characterization, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei 230031, China
Zhengqiang Li
State Environment Protection Key Laboratory of Satellite Remote Sensing, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China
Jin Hong
Key Laboratory of Optical Calibration and Characterization, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei 230031, China
Yan Ma
State Environment Protection Key Laboratory of Satellite Remote Sensing, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China
Li Li
State Environment Protection Key Laboratory of Satellite Remote Sensing, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China
Kaitao Li
State Environment Protection Key Laboratory of Satellite Remote Sensing, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China
Yizhe Fan
Key Laboratory of Optical Calibration and Characterization, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei 230031, China
Yanli Qiao
Key Laboratory of Optical Calibration and Characterization, Anhui Institute of Optics and Fine Mechanics, Chinese Academy of Sciences, Hefei 230031, China
In this paper, the feasibility of retrieving the aerosol fine-mode fraction (FMF) from ground-based sky light measurements is investigated. An inversion algorithm, based on the optimal estimation (OE) theory, is presented to retrieve FMF from single-viewing multi-spectral radiance measurements and to evaluate the impact of utilization of near-infrared (NIR) measurements at a wavelength of 1610 nm in aerosol remote sensing. Self-consistency tests based on synthetic data produced a mean relative retrieval error of 4.5%, which represented the good performance of the OE inversion algorithm. The proposed algorithm was also performed on real data taken from field experiments in Beijing during a haze pollution event. The correlation coefficients (R) for the retrieved aerosol volume fine-mode fraction (FMFv) and optical fine-mode fraction (FMFo) against AErosol RObotic NETwork (AERONET) products were 0.94 and 0.95 respectively, and the mean residual error was 4.95%. Consequently, the inversion of FMFv and FMFo could be well constrained by single-viewing multi-spectral radiance measurement. In addition, by introducing measurements of 1610 nm wavelength into the retrieval, the validation results showed a significant improvement in the R value for FMFo (from 0.89–0.94). These results confirm the high value of NIR measurements for the retrieval of coarse mode aerosols.
