Comparison and validation of band residual difference algorithm and principal component analysis algorithm for retrievals of atmospheric SO2columns from satellite observations

	Comparison and validation of band residual difference algorithm and principal component analysis algorithm for retrievals of atmospheric SO2columns from satellite observations
	Yan, Huan-Huan 1; Li, Xiao-Jing 1; Zhang, Xing-Ying 1; Wang, Wei-He 1; Chen, Liang-Fu 1; Zhang, Mei-Gen 1; Xu, Jin 1
刊名	Wuli Xuebao/Acta Physica Sinica
	2016
卷号	65 期号:8
通讯作者	Li, Xiao-Jing (lixiaoj@cma.gov.cn)
英文摘要	Remote sensing technology provides an unprecedented tool for the continuous and real-time monitoring of atmospheric SO2from volcanic eruption and anthropogenic emission. The Global Ozone Monitoring Experiment (GOME), SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY), and Ozone Monitoring Instrument (OMI) have high SO2monitoring capability. The OMI, which was launched on the EOS/Aura platform in July 2004, has the same hyperspectral measurements as the GOME and SCIAMACHY, but offers the improved spatial resolution at nadir (13 × 24 km2) and daily global coverage for short-lifetime SO2. For OMI operational SO2planetary boundary layer (PBL) retrieval, the previous band residual difference (BRD) algorithm has been replaced by principal component analysis (PCA) algorithm, which effectively reduces the systematic biases in SO2column retrievals. However, there are few studies on the evaluations and validations of PCA SO2retrievals over China, and the long-term comparisons with BRD SO2retrievals also need to be conducted. In this study, the accuracies of PCA and BRD SO2retrievals are validated by using ground-based multi axis differential optical absorption spectroscopy (MAX-DOAS) located in Beijing, and regional atmospheric modeling system, community multi-scale air quality (RAMS-CMAQ) modeling system model which can simulate the vertical distribution of atmospheric SO2. Moreover, BRD and PCA SO2retrievals from oceanic area, eastern China and Reunion volcanic eruption are compared to find the long-term trend and spatiotemporal differences between SO2columns. Finally, the uncertainty of SO2retrieval, caused by measurement errors, band selection and input parameter errors in radiative transfer model, are analysed to understand the limitations of BRD and PCA algorithms. Results show that both PCA and BRD SO2retrievals over Beijing are lower than ground-based MAX-DOAS measurements of SO2. PCA and BRD SO2retrievals over eastern China are lower than the simulated SO2columns from RAMS-CMAQ in winter 2008, but in July and August BRD SO2columns are higher than RAMS-CMAQ simulations. The values of SO2columns from BRD over China are more consistent with those from ground-based MAX-DOAS and RAMS-CMAQ model than from PCA. Although PCA algorithm effectively reduces the noise in SO2column retrieval, SO2columns from PCA over China are lower than those from BRD. For oceanic area where SO2amount is nearly zero, the standard deviation of PCA results is lower than that of BRD, but the absolute value of averaged PCA SO2column is larger than that of BRD. In the case of Reunion volcanic eruption with SO2columns larger than 25 DU, the BRD SO2columns are lower than PCA retrievals. Meanwhile, with the increase of SO2column, the difference between BRD and PCA SO2retrievals increases. Detailed uncertainty analysis shows the influences of measurement errors, band selection and inputs of radiative transfer model on the retrieval results. This study is important for developing the retrieval algorithm, and can also improve the application of OMI SO2products. © 2016 Chinese Physical Society.
收录类别	EI
语种	中文
WOS记录号	WOS:20162002392026
内容类型	期刊论文
源URL	[http://ir.radi.ac.cn/handle/183411/39645]
专题	遥感与数字地球研究所_SCI/EI期刊论文_期刊论文
作者单位	1. National Satellite Meteorological Center, China Meteorological Administration, Beijing 2.100081, China 3. State Key Laboratory of the Science of Remote Sensing, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 4.100101, China 5. State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 6.100029, China 7. Key Laboratory of Environmental Optical and Technology, Anhui Institute of Optics and Fine Mechanics, Hefei 8.230031, China
推荐引用方式 GB/T 7714	Yan, Huan-Huan,Li, Xiao-Jing,Zhang, Xing-Ying,et al. Comparison and validation of band residual difference algorithm and principal component analysis algorithm for retrievals of atmospheric SO2columns from satellite observations[J]. Wuli Xuebao/Acta Physica Sinica,2016,65(8).
APA	Yan, Huan-Huan.,Li, Xiao-Jing.,Zhang, Xing-Ying.,Wang, Wei-He.,Chen, Liang-Fu.,...&Xu, Jin.(2016).Comparison and validation of band residual difference algorithm and principal component analysis algorithm for retrievals of atmospheric SO2columns from satellite observations.Wuli Xuebao/Acta Physica Sinica,65(8).
MLA	Yan, Huan-Huan,et al."Comparison and validation of band residual difference algorithm and principal component analysis algorithm for retrievals of atmospheric SO2columns from satellite observations".Wuli Xuebao/Acta Physica Sinica 65.8(2016).