Journal article
Improving aerosol distributions below clouds by assimilating satellite-retrieved cloud droplet number
Proceedings of the National Academy of Sciences - PNAS, Vol.109(30), pp.11939-11943
07/24/2012
DOI: 10.1073/pnas.1205877109
PMCID: PMC3409723
PMID: 22778436
Abstract
Limitations in current capabilities to constrain aerosols adversely impact atmospheric simulations. Typically, aerosol burdens within models are constrained employing satellite aerosol optical properties, which are not available under cloudy conditions. Here we set the first steps to overcome the long-standing limitation that aerosols cannot be constrained using satellite remote sensing under cloudy conditions. We introduce a unique data assimilation method that uses cloud droplet number (N(d)) retrievals to improve predicted below-cloud aerosol mass and number concentrations. The assimilation, which uses an adjoint aerosol activation parameterization, improves agreement with independent N(d) observations and with in situ aerosol measurements below shallow cumulus clouds. The impacts of a single assimilation on aerosol and cloud forecasts extend beyond 24 h. Unlike previous methods, this technique can directly improve predictions of near-surface fine mode aerosols responsible for human health impacts and low-cloud radiative forcing. Better constrained aerosol distributions will help improve health effects studies, atmospheric emissions estimates, and air-quality, weather, and climate predictions.
Details
- Title: Subtitle
- Improving aerosol distributions below clouds by assimilating satellite-retrieved cloud droplet number
- Creators
- Pablo E Saide - Center for Global and Regional Environmental Research, University of Iowa, Iowa City, IA 52242, USA. pablo-saide@uiowa.eduGregory R CarmichaelScott N SpakPatrick MinnisJ Kirk Ayers
- Resource Type
- Journal article
- Publication Details
- Proceedings of the National Academy of Sciences - PNAS, Vol.109(30), pp.11939-11943
- Publisher
- United States
- DOI
- 10.1073/pnas.1205877109
- PMID
- 22778436
- PMCID
- PMC3409723
- ISSN
- 0027-8424
- eISSN
- 1091-6490
- Language
- English
- Date published
- 07/24/2012
- Academic Unit
- Civil and Environmental Engineering; Center for Global & Regional Environmental Research; Nursing; Public Policy Center (Archive); Chemical and Biochemical Engineering; School of Planning and Public Affairs
- Record Identifier
- 9983992003602771
Metrics
15 Record Views