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Advanced sensitivity analysis techniques for atmospheric chemistry models: development and application

Trace gases and aerosols, or suspended liquid and solid material in the atmosphere, have significant climatological and societal impacts; consequently, accurate representation of their contribution to atmospheric composition is vital to predicting climate change and informing policy actions. Sensitivity analysis allows scientists and environmental decision makers alike to ascertain the role a specific component of the very complex system that is the atmosphere of the Earth. Anthropogenic and natural emissions of gases and aerosol are transported by winds and interact with sunlight, allowing significant transformation before these species reach the end of their atmospheric life on land or in water. The adjoint-based sensitivity method assesses the relative importance of each emissions source to selected results of interest, including aerosol and cloud droplet concentration. In this work, the adjoint of a comprehensive inorganic aerosol thermodynamic equilibrium model was produced to improve the representativeness of regional and global chemical transport modeling. Furthermore, a global chemical transport model adjoint equipped with the adjoint of a cloud droplet activation parameterization was used to explore the footprint of emissions contributing to current and potential future cloud droplet concentrations, which impact the radiative balance of the earth. In future work, these sensitivity relationships can be exploited in optimization frameworks for assimilation of observations of the system, such as satellite-based or in situ measurements of aerosol or precursor trace gas concentrations.

Identiferoai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/51755
Date11 January 2012
CreatorsCapps, Shannon
ContributorsNenes, Athanasios, Russell, Armistead
PublisherGeorgia Institute of Technology
Source SetsGeorgia Tech Electronic Thesis and Dissertation Archive
Languageen_US
Detected LanguageEnglish
TypeDissertation

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