
Proceedings Paper
Evaluation of CALIPSO aerosol optical depth using AERONET and MODIS data over ChinaFormat | Member Price | Non-Member Price |
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Paper Abstract
Aerosol optical depth (AOD) data from Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) were inter-compared and validated against ground-based measurements from Aerosol Robotic Network (AERONET) as well as Moderate Resolution Imaging Spectroradiometer (MODIS) over China during June 2006 to December 2012. We have compared the AOD between CALIOP and AERONET site by site using quality control flags to screen the AOD data. In general, CALIOP AOD is lower than AERONET due to cloud effect detected algorithm and retrieval uncertanty. Better agreement is apparent for these sites: XiangHe, Beijing, Xinglong, and SACOL. Low correlations were observed between CALIPSO and ground-based sunphotometer data in in south or east China. Comparison results show that the overall spatio-temporal distribution of CALIPSO AOD and MODIS AOD are basically consistent. As for the spatial distribution, both of the data show several high-value regions and low-value regions in China. CALIPSO is systematically lower than MODIS over China, especially over high AOD value regions for all seasons. As for the temporal variation, both data show a significant seasonal variation: AOD is largest in spring, then less in summer, and smallest in winter and autumn. Statistical frequency analysis show that CALIPSO AOD and MODIS AOD was separated at the cut-off points around 0.2 and 0.8, the frequency distribution curves were almost the same with AOD between 0.2 and 0.8, while AOD was smaller than 0.4, CALIPSO AOD gathered at the low-value region (0-0.2) and the frequency of MODIS AOD was higher than CALIPSO AOD with AOD greater than 0.8. CALIOP AOD values show good correlation with MODIS AOD for all time scales, particularly for yearly AOD with higher correlation coefficient of 0.691. Seasonal scatterplot comparisons suggest the highest correlation coefficient of 0.749 in autumn, followed by winter of 0.665, summer of 0.566, and spring of 0.442. Evaluation of CALIOP AOD retrievals provides prospect application for CALIPSO data.
Paper Details
Date Published: 2 October 2014
PDF: 13 pages
Proc. SPIE 9221, Remote Sensing and Modeling of Ecosystems for Sustainability XI, 92210F (2 October 2014); doi: 10.1117/12.2058929
Published in SPIE Proceedings Vol. 9221:
Remote Sensing and Modeling of Ecosystems for Sustainability XI
Wei Gao; Ni-Bin Chang; Jinnian Wang, Editor(s)
PDF: 13 pages
Proc. SPIE 9221, Remote Sensing and Modeling of Ecosystems for Sustainability XI, 92210F (2 October 2014); doi: 10.1117/12.2058929
Show Author Affiliations
Chaoshun Liu, East China Normal Univ. (China)
Joint Lab. for Environmental Remote Sensing and Data Assimilation, ECNU and CEODE (China)
Xianxia Shen, East China Normal Univ. (China)
Joint Lab. for Environmental Remote Sensing and Data Assimilation, ECNU and CEODE (China)
Wei Gao, East China Normal Univ. (United States)
Joint Lab. for Environmental Remote Sensing and Data Assimilation, ECNU and CEODE (China)
Colorado State Univ. (China)
Joint Lab. for Environmental Remote Sensing and Data Assimilation, ECNU and CEODE (China)
Xianxia Shen, East China Normal Univ. (China)
Joint Lab. for Environmental Remote Sensing and Data Assimilation, ECNU and CEODE (China)
Wei Gao, East China Normal Univ. (United States)
Joint Lab. for Environmental Remote Sensing and Data Assimilation, ECNU and CEODE (China)
Colorado State Univ. (China)
Pudong Liu, East China Normal Univ. (China)
Joint Lab. for Environmental Remote Sensing and Data Assimilation, ECNU and CEODE (China)
Zhibin Sun, Colorado State Univ. (United States)
Joint Lab. for Environmental Remote Sensing and Data Assimilation, ECNU and CEODE (China)
Zhibin Sun, Colorado State Univ. (United States)
Published in SPIE Proceedings Vol. 9221:
Remote Sensing and Modeling of Ecosystems for Sustainability XI
Wei Gao; Ni-Bin Chang; Jinnian Wang, Editor(s)
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