Paper
18 November 2014 Establishing monitoring model of Haze event with multi-satellite data and application-a case: Yangtze River Delta
Binbin Jiang, Xiaoyu Zhang, Yong Du, Dasong Huang
Author Affiliations +
Abstract
Based on Aerosol Optical Thickness (AOT) in the 550nm NPP-EDR data, GOCIAOT in the 555nm for detecting and tracing sudden haze event on 2013 December in the Yangtze River Delta, while CDAS-NCEP/NCAR Reanalysis wind data is utilized to analyze the migrating routine The results show that: 1)GOCIAOT (555nm)<1 and NPPAOT (550nm)<1 is an effective indictor of distinguishing the haze event.2) The two-stream approximation algorithm can be used to retrieve GOCIAOT especially in China with high concentration of aerosol.3)Combined with high-temporal resolution of GOCIAOT is utilized for analyzing the forming mechanism of a sudden outbreak of haze event in Yangtze River Delta .The migration driven mechanism is diagnosed with CDAS-NCEP/NCAR Reanalysis wind data.4)the study suggests that the haze was formed in Hebei and Henan province on December 3, 2013.Under the strong northwest wind with the average rate of 4m/s, the haze rapidly moved to the Yangtze River Delta on December 4th2013, resulting in the most serious haze event in 2013 in there. Under the northwest wind control, the haze area expanded rapidly from 70,000km2 to 200,000km2 during its migration. The research suggests that it could be a feasible routine monitoring pattern in detecting the occurrence, migration of haze events in Yangtze River Delta.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Binbin Jiang, Xiaoyu Zhang, Yong Du, and Dasong Huang "Establishing monitoring model of Haze event with multi-satellite data and application-a case: Yangtze River Delta", Proc. SPIE 9299, International Symposium on Optoelectronic Technology and Application 2014: Optical Remote Sensing Technology and Applications, 92991C (18 November 2014); https://doi.org/10.1117/12.2073158
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Cited by 2 scholarly publications.
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KEYWORDS
Air contamination

Data modeling

Aerosols

Satellites

Atmospheric modeling

Data centers

MODIS

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