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Wildfire Smoke Particle Properties and Evolution, from Space-Based Multi-Angle ImagingEmitted smoke composition is determined by properties of the biomass burning source and ambient ecosystem. However, conditions that mediate the partitioning of black carbon (BC) and brown carbon (BrC) formation, as well as the spatial and temporal factors that drive particle evolution, are not understood adequately for many climate and air-quality related modeling applications. In situ observations provide considerable detail about aerosol microphysical and chemical properties, although sampling is extremely limited. Satellites offer the frequent global coverage that would allow for statistical characterization of emitted and evolved smoke, but generally lack microphysical detail. However, once properly validated, data from the National Aeronautics and Space Administration (NASA) Earth Observing System’s Multi-Angle Imaging Spectroradiometer (MISR) instrument can create at least a partial picture of smoke particle properties and plume evolution. We use in situ data from the Department of Energy’s Biomass Burning Observation Project (BBOP) field campaign to assess the strengths and limitations of smoke particle retrieval results from the MISR Research Aerosol (RA) retrieval algorithm. We then use MISR to characterize wildfire smoke particle properties and to identify the relevant aging factors in several cases, to the extent possible. The RA successfully maps qualitative changes in effective particle size, light absorption, and its spectral dependence, when compared to in situ observations. By observing the entire plume uniformly, the satellite data can be interpreted in terms of smoke plume evolution, including size-selective deposition, new-particle formation, and locations within the plume where BC or BrC dominates.




Document ID
20200001945
Acquisition Source
Goddard Space Flight Center
Document Type
Reprint (Version printed in journal)
External Source(s)
Authors
Noyes, Katherine Junghenn
(Maryland Univ. College Park, MD, United States)
Kahn, Ralph
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Sedlacek, Arthur
(Brookhaven National Lab. Upton, NY, United States)
Kleinman, Lawrence
(Brookhaven National Lab. Upton, NY, United States)
Limbacher, James
(Science Systems and Applications, Inc. (SSAI) Lanham, MD, United States)
Li, Zhanqing
(Maryland Univ. College Park, MD, United States)
Date Acquired
March 25, 2020
Publication Date
February 29, 2020
Publication Information
Publication: Remote Sensing
Publisher: MDPI
Volume: 12
Issue: 5
e-ISSN: 2072-4292
Subject Category
Geosciences (General)
Report/Patent Number
GSFC-E-DAA-TN79114
Report Number: GSFC-E-DAA-TN79114
E-ISSN: 2072-4292
Funding Number(s)
CONTRACT_GRANT: NNX17AE79A
CONTRACT_GRANT: NNG17HP01C
Distribution Limits
Public
Copyright
Public Use Permitted.
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