Journal article
Evaluation of aerosol optical depth and aerosol models from VIIRS retrieval algorithms over North China Plain
Remote sensing (Basel, Switzerland), Vol.9(5), p.432
2017
DOI: 10.3390/rs9050432
PMCID: PMC6003421
PMID: 29910965
Abstract
The first Visible Infrared Imaging Radiometer Suite (VIIRS) was launched on Suomi National Polar-orbiting Partnership (S-NPP) satellite in late 2011. Similar to the Moderate resolution Imaging Spectroradiometer (MODIS), VIIRS observes top-of-atmosphere spectral reflectance and is potentially suitable for retrieval of the aerosol optical depth (AOD). The VIIRS Environmental Data Record data (VIIRS_EDR) is produced operationally by NOAA, and is based on the MODIS atmospheric correction algorithm. The "MODIS-like" VIIRS data (VIIRS_ML) are being produced experimentally at NASA, from a version of the "dark-target" algorithm that is applied to MODIS. In this study, the AOD and aerosol model types from these two VIIRS retrieval algorithms over the North China Plain (NCP) are evaluated using the ground-based CE318 Sunphotometer (CE318) measurements during 2 May 2012 - 31 March 2014 at three sites. These sites represent three different surface types: urban (Beijing), suburban (XiangHe) and rural (Xinglong). Firstly, we evaluate the retrieved spectral AOD. For the three sites, VIIRS_EDR AOD at 550 nm shows a positive mean bias (MB) of 0.04-0.06 and the correlation of 0.83-0.86, with the largest MB (0.10-0.15) observed in Beijing. In contrast, VIIRS_ML AOD at 550 nm has overall higher positive MB of 0.13-0.14 and a higher correlation (0.93-0.94) with CE318 AOD. Secondly, we evaluate the aerosol model types assumed by each algorithm, as well as the aerosol optical properties used in the AOD retrievals. The aerosol model used in VIIRS_EDR algorithm shows that dust and clean urban models were the dominant model types during the evaluation period. The overall accuracy rate of the aerosol model used in VIIRS_ML over NCP three sites (0.48) is higher than that of VIIRS_EDR (0.27). The differences in Single Scattering Albedo (SSA) at 670 nm between VIIRS_ML and CE318 are mostly less than 0.015, but high seasonal differences are found especially over the Xinglong site. The values of SSA from VIIRS_EDR are higher than that observed by CE318 over all sites and all assumed aerosol modes, with a positive bias of 0.02-0.04 for fine mode, 0.06-0.12 for coarse mode and 0.03-0.05 for bi-mode at 440nm. The overestimation of SSA but positive AOD MB of VIIRS_EDR indicate that other factors (e.g. surface reflectance characterization or cloud contamination) are important sources of error in the VIIRS_EDR algorithm, and their effects on aerosol retrievals may override the effects from non-ideality in these aerosol models.
Details
- Title: Subtitle
- Evaluation of aerosol optical depth and aerosol models from VIIRS retrieval algorithms over North China Plain
- Creators
- Jun Zhu - University of Chinese Academy of Sciences, Beijing 100049, ChinaXiangao Xia - University of Chinese Academy of Sciences, Beijing 100049, ChinaJun Wang - Department of Chemical and Biochemical Engineering, Univ. of Iowa, Iowa City, Iowa, USAHuizheng Che - LAC, Chinese Academy of Meteorological Sciences (CAMS), CMA, Beijing, 100081, ChinaHongbin Chen - LAGEO, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, ChinaJinqiang Zhang - LAGEO, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, ChinaXiaoguang Xu - Department of Chemical and Biochemical Engineering, Univ. of Iowa, Iowa City, Iowa, USARobert Levy - Laboratory for Radiation and Climate, NASA GSFC, Greenbelt, Maryland, USAMin Oo - University of Wisconsin-Madison, Madison, Wisconsin, USARobert Holz - University of Wisconsin-Madison, Madison, Wisconsin, USAMohammed Ayoub - Qatar Environment & Energy Research Institute, Qatar Foundation, Qatar
- Resource Type
- Journal article
- Publication Details
- Remote sensing (Basel, Switzerland), Vol.9(5), p.432
- DOI
- 10.3390/rs9050432
- PMID
- 29910965
- PMCID
- PMC6003421
- NLM abbreviation
- Remote Sens (Basel)
- ISSN
- 2072-4292
- eISSN
- 2072-4292
- Language
- English
- Date published
- 2017
- Academic Unit
- Civil and Environmental Engineering; Iowa Technology Institute; Physics and Astronomy; Chemical and Biochemical Engineering
- Record Identifier
- 9984104912702771
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