Global Aerosol Type Maps: The Next Generation

Global Aerosol Optical Depth (AOD) products have received vastly more attention from satellite instrument teams than aerosol type and aerosol microphysical property data products, despite their importance for many climate and air-quality related applications. This is largely because aerosol properties are much more difficult to retrieve from remote sensing than AOD. Even multi-angle instruments, such as the NASA Earth Observing System’s Multi-angle Imaging SpectroRadiometer (MISR), contain only qualitative constraints on aerosol size, shape, and single-scattering albedo (SSA). The quality of aerosol type retrievals is much more dependent on observing conditions than for AOD; they require significantly greater absolute and especially channel-to-channel relative calibration accuracy, as well as much more accurate, and generally self-consistent, surface bi-directional reflectance distribution function (BRDF) characterization. Further, except for spectral AOD from surface-based sun photometers such as AERONET, the primary source of particle property “ground truth” is from rare field campaign golden days.

Ongoing work with MISR in this area is supported by the NASA Atmospheric Composition Modeling and Analysis Program (ACMAP). A detailed analysis of the MISR Standard aerosol-type product showed both the strengths and limitations of the retrieved aerosol type information, including the degree to which each of particle sphericity, size, and absorption are constrained under a range of observing conditions [Kahn and Gaitley, JGR 2015]. Using the MISR Research Aerosol Retrieval algorithm (RA), we explored the possibilities for improving upon the standard product over ocean with radiometric calibration refinement, better surface modeling, adjustments to the radiance selection, enhanced cloud screening, adaptive solution-acceptance criteria, and an improved climatology of aerosol types and mixtures in the algorithm [Limbacher and Kahn, 2014; 2015; 2017]. In this presentation, we will summarize our recent work under the ACMAP program, including the status of our improved aerosol type retrieval algorithm, efforts to improve RA throughput, further product validation, and application of the enhanced product to air quality and volcanic plume studies.

References

Kahn, R. A., and B. J. Gaitley, 2015. An analysis of global aerosol type as retrieved by MISR. J. Geophys. Res. Atmos. 120, doi:10.1002/2015JD023322.

Limbacher, J.A., and R.A. Kahn, 2014. MISR Research-Aerosol-Algorithm: Refinements For Dark Water Retrievals. Atm. Meas. Tech. 7, 1-19, doi:10.5194/amt-7-1-2014.

Limbacher, J.A., and R.A. Kahn, 2015. MISR Empirical Stray Light Corrections in High-Contrast Scenes. Atmos. Meas. Tech. 8, doi: 10.5194/amt-8-1-2015.

Limbacher, J.A., and R.A. Kahn, 2017. Updated MISR dark water research aerosol retrieval algorithm – Coupled 1.1 km ocean surface Chlorophyll-a retrievals with empirical calibration corrections. Atmos. Meas. Tech. 10, 1539–1555, doi:10.5194/amt-10-1539-2017

Flower, V., and R.A. Kahn, 2017b. Distinguishing remobilized ash from erupted volcanic plumes using 1 space-borne multi-angle imaging. Geophys. Res. Lett.. (submitted)

Flower, V., and R.A. Kahn, 2017. Tracking microphysical variations in emissions from Karymsky volcano, using MISR multi-angle imagery. (in preparation)

Friberg, M.D., R.A. Kahn, et al., 2017. Surface aerosol airmass type mapping over the San Joaquin airshed basin using space-based multi-angle imaging and chemical transport modeling. Atmosph. Chem. Phys. (in preparation)