Gone with the Wind: The Trans-Pacific Journey of Atmospheric Particles
Dust particles from African and Asian deserts can travel long distances through the atmosphere, but a lack of integrated observations has made it difficult to assess the complex and size-dependent processes associated with dust emission, transport, and removal.
A study led by researchers at the U.S. Department of Energy’s (DOE) Pacific Northwest National Laboratory (PNNL) provided new insight into the evolution of large dust particles during their trans-Pacific voyage from Asia and Africa to the Rocky Mountains. Researchers concluded that these particles might remain suspended in the atmosphere longer and travel remarkably farther than anticipated — thousands rather than hundreds of kilometers. The observed quasi-static behavior of these particles over the transport processing time could lead to more realistic treatment of their evolution in climate models to advance understanding of dust effects on climate at regional and global scales.
Many atmospheric processes, such as long-range transport of particles and their removal from the atmosphere by rain and snow, strongly depend on the particle size. Large particles are more susceptible to this removal than smaller ones. Current climate models have a simplified representation of these complex and size-dependent processes. Findings from this study showed that high-altitude winds over the Pacific Ocean carried particles from remote desert areas in Asia and Africa to the western United States. Plumes occasionally observed over ski resorts in Colorado during winter and spring hold many of these dust particles. Using ground-based data collected from the high-elevation Storm Peak Laboratory and the nearby Atmospheric Radiation Measurement (ARM) Mobile Facility in Colorado, the research team found that the lifetime of the larger dust particles transported from Asia and Africa is longer than previously expected from climate model predictions. The researchers developed a framework with strongly linked observational and modeling components, and demonstrated that it has the potential to estimate uncertainties of climate model predictions associated with transport-related processes.