气候变化领域集成服务门户(CCPortal): Improvement of snow/haze confusion data gaps in MODIS Dark Target aerosol retrievals in East China

CCPortal

DOI	10.1016/j.atmosres.2020.105063
	Improvement of snow/haze confusion data gaps in MODIS Dark Target aerosol retrievals in East China
	Zhang X.; Wang H.; Che H.-Z.; Tan S.-C.; Shi G.-Y.; Yao X.-P.; Zhao H.-J.
发表日期	2020
ISSN	0169-8095
卷号	245
英文摘要	The MODerate resolution Imaging Spectroradiometer (MODIS) is one of the most widely used meteorological remote sensing instruments. Its Dark Target aerosol optical depth (AOD) product has been widely used in environment and meteorology researches, such as model evaluation and data assimilation. However, this product has a low coverage under conditions of heavy haze in China. This is because the haze can be misidentified as snow under some circumstances by the algorithm and therefore rejected, leading to large-scale data omission. In the most polluted regions, misidentified snow cover exceeded 8%. Regarding this issue, a new method combining the snow mask derived from the MODIS cloud mask product and Fisher discrimination analysis was developed to give a more accurate identification of snow and ice cover. Applying this new method increases the AOD data coverage significantly. Comparisons with AOD values from ground-based observations showed that the newly produced data under haze conditions had a similar accuracy with the original data in the MODIS AOD product. Because the newly supplemented data are more distributed at the seriously polluted regions, the average AOD increased significantly after data filling in many regions. In winter, AOD in the most severely polluted regions (average air quality index >130) increased by 0.2–0.3 after improvement, about 30–50% of the original value. In 49 haze cases with large-scale pollution, the increase reached 0.3–0.6, about 50%–70% of the original value. During the haze episodes, the data omission led to an underestimation of the regional average AOD by 19–40%. The improvement in AOD coverage helps to provide a better reflection of the air pollution condition in East China through the perspective of AOD. © 2020
英文关键词	Aerosol optical depth; Air pollution; East China; MODIS; Snow and ice cover
语种	英语
scopus关键词	Aerosols; Air quality; Radiometers; Remote sensing; Aerosol optical depths; Air quality indices; Cloud mask products; Data assimilation; Fisher discrimination; Ground-based observations; Moderate resolution imaging spectroradiometer; Remote sensing instruments; Snow; aerosol; air quality; data assimilation; haze; ice cover; MODIS; optical depth; snow cover; China
来源期刊	Atmospheric Research
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/141821
作者单位	State Key Laboratory of Severe Weather (LASW), Chinese Academy of Meteorological Sciences (CAMS), CMA, Beijing, 100081, China; Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology, Nanjing, 210044, China; State Key Laboratory of Numerical Modeling of Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China; China Meteorological Administration Training Centre, CMA, Beijing, 100081, China; Institute of Atmospheric Environment, China Meteorological Administration, Shenyang, 110016, China
推荐引用方式 GB/T 7714	Zhang X.,Wang H.,Che H.-Z.,et al. Improvement of snow/haze confusion data gaps in MODIS Dark Target aerosol retrievals in East China[J],2020,245.
APA	Zhang X..,Wang H..,Che H.-Z..,Tan S.-C..,Shi G.-Y..,...&Zhao H.-J..(2020).Improvement of snow/haze confusion data gaps in MODIS Dark Target aerosol retrievals in East China.Atmospheric Research,245.
MLA	Zhang X.,et al."Improvement of snow/haze confusion data gaps in MODIS Dark Target aerosol retrievals in East China".Atmospheric Research 245(2020).