Jaehwa Lee 1,2, N. Christina Hsu1, Corey Bettenhausen1,3, Andrew M. Sayer1,4, Colin J. Seftor1,3, Myeong-Jae Jeong5, Si-Chee Tsay1, Ellsworth J. Welton1, Sheng-Hsiang Wang6, Wei-Nai Chen7
Cite this article: Lee, J., Hsu, N.C., Bettenhausen, C., Sayer, A.M., Seftor, C.J., Jeong, M.J., Tsay, S.C., Welton, E.J., Wang, S.H. and Chen, W.N. (2016). Evaluating the Height of Biomass Burning Smoke Aerosols Retrieved from Synergistic Use of Multiple Satellite Sensors over Southeast Asia.
Aerosol Air Qual. Res.
16: 2831-2842. https://doi.org/10.4209/aaqr.2015.08.0506
HIGHLIGHTS
Satellite retrievals of aerosol SSA and height are performed over Southeast Asia.
Retrieval results are compared to data from spaceborne and ground-based instruments.
Satellite-retrieved SSA and height show promising performance.
ABSTRACT
This study evaluates the height of biomass burning smoke aerosols retrieved from a combined use of Visible Infrared Imaging Radiometer Suite (VIIRS), Ozone Mapping and Profiler Suite (OMPS), and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) observations. The retrieved heights are compared against spaceborne and ground-based lidar measurements during the peak biomass burning season (March and April) over Southeast Asia from 2013 to 2015. Based on the comparison against CALIOP, a quality assurance (QA) procedure is developed. It is found that 74% (81–84%) of the retrieved heights fall within 1 km of CALIOP observations for unfiltered (QA-filtered) data, with root-mean-square error (RMSE) of 1.1 km (0.8–1.0 km). Eliminating the requirement for CALIOP observations from the retrieval process significantly increases the temporal coverage with only a slight decrease in the retrieval accuracy; for best QA data, 64% of data fall within 1 km of CALIOP observations with RMSE of 1.1 km. When compared with Micro-Pulse Lidar Network (MPLNET) measurements deployed at Doi Ang Khang, Thailand, the retrieved heights show RMSE of 1.7 km (1.1 km) for unfiltered (QA-filtered) data for the complete algorithm, and 0.9 km (0.8 km) for the simplified algorithm.
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