Atmos. Chem. Phys. Discuss., 10, 10777-10837, 2010
www.atmos-chem-phys-discuss.net/10/10777/2010/
doi:10.5194/acpd-10-10777-2010
© Author(s) 2010. This work is distributed
under the Creative Commons Attribution 3.0 License.
Review Status
This discussion paper has been under review for the journal Atmospheric Chemistry and Physics (ACP). Please refer to the corresponding final paper in ACP.
Quantifying the sub-grid variability of trace gases and aerosols based on WRF-Chem simulations
Y. Qian, W. I. Gustafson Jr., and J. D. Fast
Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory, Washington, USA

Abstract. One fundamental property and limitation of grid based models is their inability to identify spatial details smaller than the grid cell size. While decades of work have gone into developing sub-grid treatments for clouds and land surface processes in climate models, the quantitative understanding of sub-grid processes and variability for aerosols and their precursors is much poorer. In this study, WRF-Chem is used to simulate the trace gases and aerosols over central Mexico during the 2006 MILAGRO field campaign, with multiple spatial resolutions and emission/terrain scenarios. Our analysis focuses on quantifying the sub-grid variability (SGV) of trace gases and aerosols within a typical global climate model grid cell, i.e. 75×75 km2.

Our results suggest that a simulation with 3-km horizontal grid spacing adequately reproduces the overall transport and mixing of trace gases and aerosols downwind of Mexico City, while 75-km horizontal grid spacing is insufficient to represent local emission and terrain-induced flows along the mountain ridge, subsequently affecting the transport and mixing of plumes from nearby sources. Therefore, the coarse model grid cell average may not correctly represent aerosol properties measured over polluted areas. Probability density functions (PDFs) for trace gases and aerosols show that secondary trace gases and aerosols, such as O3, sulfate, ammonium, and nitrate, are more likely to have a relatively uniform probability distribution (i.e. smaller SGV) over a narrow range of concentration values. Mostly inert and long-lived trace gases and aerosols, such as CO and BC, are more likely to have broad and skewed distributions (i.e. larger SGV) over polluted regions. Over remote areas, all trace gases and aerosols are more uniformly distributed compared to polluted areas. Both CO and O3 SGV vertical profiles are nearly constant within the PBL during daytime, indicating that trace gases are very efficiently transported and mixed vertically by turbulence. But, simulated horizontal variability indicates that trace gases and aerosols are not well mixed horizontally in the PBL. During nighttime the SGV for trace gases is maximum at the surface, and quickly decreases with height. Unlike the trace gases, the SGV of BC and secondary aerosols reaches a maximum at the PBL top during the day. The SGV decreases with distance away from the polluted urban area, has a more rapid decrease for long-lived trace gases and aerosols than for secondary ones, and is greater during daytime than nighttime.

The SGV of trace gases and aerosols is generally larger than for meteorological quantities. Emissions can account for up to 50% of the SGV over urban areas such as Mexico City during daytime for less-reactive trace gases and aerosols, such as CO and BC. The impact of emission spatial variability on SGV decays with altitude in the PBL and is insignificant in the free troposphere. The emission variability affects SGV more significantly during daytime (rather than nighttime) and over urban (rather than rural or remote) areas. The terrain, through its impact on meteorological fields such as wind and the PBL structure, affects dispersion and transport of trace gases and aerosols and their SGV.


Citation: Qian, Y., W. I. Gustafson Jr., and Fast, J. D.: Quantifying the sub-grid variability of trace gases and aerosols based on WRF-Chem simulations, Atmos. Chem. Phys. Discuss., 10, 10777-10837, doi:10.5194/acpd-10-10777-2010, 2010.
 
Search ACPD
Discussion Paper
    XML
    Citation
    Final Revised Paper
    Share