15 January 2014

Size Matters: Modeling Dust Mass Balance and Radiative Forcing


Putting a climate model through some dusty drills, scientists at Pacific Northwest National Laboratory found how well it depicts the climate effects of particle size. Comparing three techniques to represent the particles' size distribution, they found a large difference among them—by a factor of 10—in the amount of cooling that dust provides at the top of the atmosphere. They also found large differences in the impact of dust size on the surface cooling and atmospheric warming. Their study, published in Atmospheric Chemistry and Physics, drives further examination of how desert-born particles impact climate, air quality and the ecosystem.


Rising and blowing from world deserts, dust can travel hundreds of miles affecting health, the environment and the climate of distant regions. Deserts cover about one-third of the Earth's surface and in some parts of the world, a dust storm can block sunlight for days, showing its ability to mask, reflect and scatter sunlight. But even when these effects aren't apparent to the eye, plumes of desert dust are working their far-reaching effects high in the atmosphere. Desert dust is considered a major contributor to the total atmospheric particle burden, and thus, plays a major role in regional and global climate systems and air quality. The PNNL research is part of a stepped approach to ascertain how dust is accounted for in a climate model, and then quantify how dust, often transported over long distances, impacts regional and global climate.


Using the Weather Research and Forecasting-Chemistry (WRF-Chem) model, a meteorological and chemistry model, the PNNL-led team conducted quasi-global simulations with three different approaches to represent dust size: 8 discrete bins (8-bin), 4 discrete bins (4-bin), and 3 log-normal mode (3-mode). They identified and quantified biases in the 3-mode and 4-bin approaches compared to the more accurate 8-bin approach in simulating the dust mass balance and radiative forcing.

Their results quantified the different approaches' abilities to represent the dust lifetime, dust mass loading, dry and wet deposition fluxes and dust number concentrations. They found that the aerosol optical depth among the three size approaches is much larger than their difference in dust mass loading. On a quasi-global average, the three approaches show a significant difference in dust surface cooling and atmospheric warming, with a large difference, by a factor of ~10, in the dust cooling at the top of the atmosphere.


Dust plays an important role in the regional and global climate system and has significant impacts on air quality. In new research led by U.S. Department of Energy scientists at Pacific Northwest National Laboratory, the team examined uncertainties in simulating mineral dust mass balance and radiative forcing due to biases in the dust size parameterizations. In quasi-global simulations using the WRF-Chem model they applied three different approaches to represent dust size distributions. The comparison of multiple simulations shows that the uncertainty in dust mass loading is within 25%, but the dust number loading could differ by up to a factor of 100. The dust mass and number loading simulated by the three approaches showed large spatial differences, particularly in regions remote from the sources. The three size parameterizations also resulted in significantly different dry and wet deposition fluxes. Among the simulations, dust surface cooling and atmospheric warming effects could differ by a factor of 2~3 and the dust top-of-atmosphere cooling effect could differ by a factor of ~10. The team suggests further investigation on the model bias in simulating dust impact on climate that resulted from inappropriately representing dust size distributions.

C Zhao
Pacific Northwest National Laboratory (PNNL)
Zhao, C, S Chen, LR Leung, Y Qian, JF Kok, RA Zaveri, and J Huang.  2013.  "Uncertainty in Modeling Dust Mass Balance and Radiative Forcing from Size Parameterization."  Atmospheric Chemistry and Physics 10733-10753, doi:10.5194/acp-13-10733-2013.

This research was supported by the U.S. Department of Energy's (DOE's) Office of Science, Biological and Environmental Research program as part of the Regional & Global Climate Modeling (RGCM) program and the National Science Foundation. This study used computing resources from the National Energy Research Scientific Computing Center, which is supported by the DOE Office of Science.