SAM-CAAM: A Concept for Acquiring Systematic Aircraft Measurements to Characterize Aerosol Air Masses
Abstract
A modest operational program of systematic aircraft measurements can resolve key satellite aerosol data record limitations. Satellite observations provide frequent global aerosol amount maps but offer only loose aerosol property constraints needed for climate and air quality applications. We define and illustrate the feasibility of flying an aircraft payload to measure key aerosol optical, microphysical, and chemical properties in situ. The flight program could characterize major aerosol airmass types statistically, at a level of detail unobtainable from space. It would 1) enhance satellite aerosol retrieval products with better climatology assumptions and 2) improve translation between satellite-retrieved optical properties and species-specific aerosol mass and size simulated in climate models to assess aerosol forcing, its anthropogenic components, and other environmental impacts. As such, Systematic Aircraft Measurements to Characterize Aerosol Air Masses (SAM-CAAM) could add value to data records representing several decades of aerosol observations from space; improve aerosol constraints on climate modeling; help interrelate remote sensing, in situ, and modeling aerosol-type definitions; and contribute to future satellite aerosol missions. Fifteen required variables are identified and four payload options of increasing ambition are defined to constrain these quantities. "Option C" could meet all the SAM-CAAM objectives with about 20 instruments, most of which have flown before, but never routinely several times per week, and never as a group. Aircraft integration and approaches to data handling, payload support, and logistical considerations for a long-term, operational mission are discussed. SAM-CAAM is feasible because, for most aerosol sources and specified seasons, particle properties tend to be repeatable, even if aerosol loading varies.
Additional Information
© 2017 American Meteorological Society. Final Form: 7 March 2017; Published online: 30 October 2017. Publisher's Note: This article was revised on 24 October 2017 to add affiliation for D. M. Murphy. We thank Mike Cropper, Ed Eloranta, John Hair, Raymond Hoff, Martin Nowicki, and Ellsworth J. Welton for consultation on instrument and aircraft specifics; Po-Lun Ma for the model simulation shown in Fig. ES1; and Christy Hansen and Hal Maring for encouragement and advice. The work of R. Kahn is supported at the NASA Goddard Space Flight Center in part by NASA's Climate and Radiation Research and Analysis Program, under H. Maring; NASA's Atmospheric Composition Program under R. Eckman; and the NASA ACE mission science definition initiative. The work of Steven Ghan is supported at the Pacific Northwest National Laboratory, operated for DOE by Battelle Memorial Institute under Contract DE-AC06-76RLO 1830.Attached Files
Published - bams-d-16-0003.1.pdf
Accepted Version - nihms928322.pdf
Supplemental Material - 10.1175_bams-d-16-0003.2_si.pdf
Files
Additional details
- PMCID
- PMC5745363
- Eprint ID
- 83255
- Resolver ID
- CaltechAUTHORS:20171116-112429011
- NASA
- DE-AC06-76RLO 1830
- Department of Energy (DOE)
- Created
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2017-11-16Created from EPrint's datestamp field
- Updated
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2022-03-21Created from EPrint's last_modified field