MAIAC Thermal Technique for Smoke Injection Height From MODIS
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Author/Creator ORCID
Date
2019-09-12
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Citation of Original Publication
A. Lyapustin, Y. Wang, S. Korkin, R. Kahn and D. Winker, "MAIAC Thermal Technique for Smoke Injection Height From MODIS," in IEEE Geoscience and Remote Sensing Letters, vol. 17, no. 5, pp. 730-734, May 2020, doi: 10.1109/LGRS.2019.2936332.
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This work was written as part of one of the author's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 U.S.C. 105, no copyright protection is available for such works under U.S. Law.
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Abstract
We present a new algorithm to derive smoke plume height (H a ) using the thermal contrast from the rising mixture of aerosol and emitted gases in the Moderate Resolution Imaging Spectroradiometer (MODIS) 11-μm channel. Validation shows good agreement with the wind-corrected Multi-angle Imaging SpectroRadiometer (MISR)-MISR Interactive Explorer (MINX) values, with about 60% of the MODIS Terra thermal retrievals within 500 m of MISR H ᵃ and 450 m lower on average. The bias is expected because the thermal technique represents an effective rather than a top plume height from MISR MINX. The comparison of MODIS Aqua retrievals with Cloud-Aerosol LiDAR with Orthogonal Polarization (CALIOP) Cloud-Aerosol LiDAR and Infrared Pathfinder Satellite Observations (CALIPSO) shows similar statistics, with a standard deviation of 458 m for the mean plume height and 216 m lower on average. Ha is part of the MultiAngle Implementation of Atmospheric Correction (MAIAC) MODIS Collection 6 suite of products (MCD19), accessible via the Land Product Distributed Active Archive Center (LP DAAC). Aerosol injection height is reported in the daily MAIAC atmospheric product MCD19A2 along with the cloud mask (CM), column water vapor, aerosol optical depth (AOD), AOD uncertainty, and aerosol type, at 1-km resolution on a global sinusoidal grid. Despite some limitations, the vastly increased coverage from MODIS observations makes it a valuable data set complementing the established MISR and CALIOP products.