The potential of atmospheric dust aerosols to modify the Earth's environment and climate has been recognized for some time. However, predicting the diverse impact of dust has several significant challenges. One is to quantify the complex spatial and temporal variability of dust burden in the atmosphere. Another is to quantify the fraction of dust originating from human-made sources.
This thesis focuses on the spatiotemporal characterization of sources and dust outbreaks in Central and East Asia by integrating ground-based data, satellite multi-sensor observations, and modeling. A new regional dust modeling system capable of operating over a span of scales was developed. The modeling system consists of a dust module DuMo, which incorporates several dust emission schemes of different complexity, and the PSU/NCAR mesoscale model MM5, which offers a variety of physical parameterizations and flexible nesting capability.
The modeling system was used to perform for the first time a comprehensive study of the timing, duration, and intensity of individual dust events in Central and East Asia. Determining the uncertainties caused by the choice of model physics, especially the boundary layer parameterization, and the dust production scheme was the focus of our study. Implications to assessments of the anthropogenic dust fraction in these regions were also addressed.
Focusing on Spring 2001, an analysis of routine surface meteorological observations and satellite multi-sensor data was carried out in conjunction with modeling to determine the extent to which to this integrated data set can be used to characterize the spatiotemporal distribution of dust plumes at a range of temporal scales, addressing the active dust sources in China and Mongolia, mid-range transport and trans-Pacific, long-range transport of dust outbreaks on a case-by-case basis.
This work demonstrates that adequate and consistent characterization of individual dust events is central to establishing a reliable climatology, ultimately leading to improved assessments of dust impacts on the environment and climate. This will also help to identify the appropriate temporal and spatial scales for adequate intercomparison between model results and observational data as well as for developing an integrated analysis methodology for dust studies.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/10512 |
| Date | 07 April 2006 |
| Creators | Darmenova, Kremena |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Language | en_US |
| Detected Language | English |
| Type | Dissertation |
| Format | 7348619 bytes, application/pdf |
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