Paper
14 October 2004 A modeling approach for aerosol optical depth analysis during forest fire events
Martin P. Aube, Normand T. O'Neill, Alain Royer, David Lavoue
Author Affiliations +
Abstract
Measurements of aerosol optical depth (AOD) are important indicators of aerosol particle behavior. Up to now the two standard techniques used for retrieving AOD are; (i) sun photometry which provides measurements of high temporal frequency and sparse spatial frequency, and (ii) satellite based approaches such as DDV (Dense Dark Vegetation) based inversion algorithms which yield AOD over dark targets in remotely sensed imagery. Although the latter techniques allow AOD retrieval over appreciable spatial domains, the irregular spatial pattern of dark targets and the typically low repeat frequencies of imaging satellites exclude the acquisition of AOD databases on a continuous spatio-temporal basis. We attempt to fill gaps in spatio-temporal AOD measurements using a new assimilation methodology that links AOD measurements and the predictions of a particulate matter Transport Model. This modelling package (AODSEM V2.0 for Aerosol Optical Depth Spatio-temporal Evolution Model) uses a size and aerosol type segregated semi-Lagrangian trajectory algorithm driven by analysed meteorological data. Its novelty resides in the fact that the model evolution may be tied to both ground based and satellite level AOD measurement and all physical processes have been optimized to track this important and robust parameter. We applied this methodology to a significant smoke event that occurred over the eastern part of North America in July 2002.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Martin P. Aube, Normand T. O'Neill, Alain Royer, and David Lavoue "A modeling approach for aerosol optical depth analysis during forest fire events", Proc. SPIE 5548, Atmospheric and Environmental Remote Sensing Data Processing and Utilization: an End-to-End System Perspective, (14 October 2004); https://doi.org/10.1117/12.558715
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Cited by 1 scholarly publication.
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KEYWORDS
Aerosols

Atmospheric modeling

Data modeling

Atmospheric particles

MODIS

Databases

Satellites

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