Capabilities of the WRF-Chem model in estimating the concentration of dust – A case study of a dust storm in Tehran

Document Type : علمی - پژوهشی


Atmospheric Chemistry and Air Pollution Research Group, Atmospheric Science and Meteorological Research Center (ASMERC)


Introduction: Although in recent years several dust models have been investigated for the Middle East, we need to undertake more studies on verification of dust numerical models for the Middle East given the vast expansion of the region and the creation of new dust sources. Several researchers such as Marticorena and Bergametti (1995), Shao et al. (1996), Marticorena et al. (1997), and Shao et al. (2004) have contributed to the development of integrated physical wind erosion models which can be coupled with meteorological models. The parameterizations used in these models include processes such as salination and creep of sand particles.Materials and methods: In this study, numerical simulation and observational techniques were used in order to analyze the dust storm that occurred in Tehran on June 2nd. 2014. The WRF/Chem V3.6.1 model was carried out for two days from 1 to 3 June 2014 by GFS analysis data for the initial and boundary conditions. For this study, an advanced MADE-SORGAM scheme such as the aerosol scheme was used. This scheme is based on the dynamic modal model for particulate matters in Europe. Particulate matters in the MADE aerosol scheme are modelled in the three modes of Aitken (less than 0.1 micro-meter), accumulation (between 01 to 2 micrometers) and coarse (greater than 2 micro-meters).Results and discussion: For the verification of the model WRF/Chem using post-processing programmemes, PM10 distribution maps are provided alongsides its concentration. The coupling of the small-scale deformation field with a lower tropospheric cool pool as a result of mid-tropospheric cloud precipitation resulted in the genesis of Tehran’s dust storm. The results of the model WRF/Chem for PM10 and the surface winds on 2 June 2017 is shown. In terms of dust distribution, the model could determine the main internal dust source and differentiate it from the dust mass originating from eastern Iraq. Because of some limitations in the MADE aerosol scheme for the regions with high topographical features, its results might show over- and/or underestimations. Also if there are errors in the land use data and the erosion properties of soil, the model results may show a discrepancy from the real measurements. Some regions of the simulation domain such as the eastern Caspian Sea and Turkmenistan often show a high concentration of dust which, by comparing them to optical thickness data of MODIS satellite, is determined to be consistent with reality. Conclusion: In general, the results of the WRF/Chem model in this study proves its practical aspects and capability in modelling and predicting of air quality, especially for dust particles from natural emission sources such as aeolian and erodible soils. There have been considerable changes in land use and the likelihood of erosion of soils in recent years due to factors such as climate change and vegetation loss in the Middle East region. However, the geographical data used in the pre-processing unit of the WRF model belongs to previous years and this can result in errors in the results; therefore, consideration of the fact that, on the regional scale, the geographical data with high impact in dust emission modelling must be enhanced and corrected is of great importance.


  1. Ackermann, I.J., Hass, H., Memmesheimer, M., Ebel, A., Binkowski, F.S., and Shankar, U., 1998. Modal Aerosol Dynamics model for Europe: Development and first applications. Atmospheric Environment. 32(17), 2981–2999.
  2. Binkowski, F.S., and Shankar, U, 1995. The Regional Particulate Matter Model. 1. Model description and preliminary results. Journal of Geophysical Research. 100(D12), 26191–26209.
  3. Forkel, R., Werhahn, J., McKeen, S.A., Peckham, S.E., Grell, G.A., and Suppan, P., 2013. A Case Study on the Impact of Aerosol-Radiation Feedback on Meteorology and Regional Pollutant Distributions. NATO Science for Peace and Security Series C: Environmental Security. 137, 357–361.
  4. Grell, G.A., Peckham, S.E., Schmitz, R., McKeen, S.A., Frost, G., Skamarock, W.C., and Eder, B. 2005. Fully coupled “online” chemistry within the WRF model. Atmospheric Environment. 39(37), 6957–6975.
  5. Hamidi, M., Kavianpour, M.R., and Shao, Y. 2014. Numerical simulation of dust events in the Middle East. Aeolian Research. 13, 59–70.
  6. Hsu, N.C., Gautam, R., Sayer, A.M., ettenhausen, C., Li, C., Jeong, M.J., Tsay, S.C. and Holben, B.N., 2012. Global and regional trends of aerosol optical depth over land and ocean using SeaWiFS measurements from 1997 to 2010. Atmospheric Chemistry and Physics. 12, 8037– 8053.
  7. Levy, R.C. Remer L.A., Kleidman R.G., attoo,S. C. Ichoku, R. Kahn, and Eck, T. F., 2010. Global evaluation of the Collection 5 MODIS dark-target aerosol products over land, Atmospheric Chemistry and Physics. 10, 10399-10420.
  8. Li, G., Bei, N., Tie, X., and Molina, L.T., 2011. Aerosol effects on the photochemistry in Mexico City during MCMA-2006/MILAGRO campaign. Atmospheric Chemistry and Physics, 11(11), 5169–5182.
  9. Marticorena, B., and Bergametti, G., 1995. Modeling the Atmospheric Dust Cycle .1. Design of a Soil-Derived Dust Emission Scheme. Journal of Geophysical Research-Atmospheres.
  10. Moridnejad, A., Karimi, N., and Ariya, P.A., 2015. Newly desertified regions in Iraq and its surrounding areas: Significant novel sources of global dust particles. Journal of Arid Environments.116, 1–10.
  11. Park, S.U., Ju, J.W., Lee, I.H., and Joo, S.J., 2016. A parameterization of dust emission (PM10) fluxes of dust events observed at Naiman in Inner Mongolia using the monitored tower data. Atmospheric Environment. 140, 420-431.
  12. Prakash, J., Stenchikov, G., Kalenderski, S., Osipov, S., and Bangalath, H., 2015. The impact of dust storms on the Arabian Peninsula and the Red Sea. Atmospheric Chemistry and Physics. 15(1), 199–222.
  13. Schell, B., Ackermann, I.J., Hass, H., Binkowski, F. S., and Ebel, A., 2001. Modeling the formation of secondary organic aerosol within a comprehensive air quality model system. DOI: 10.1029/2001JD000384
  14. Shao, Y. (2004). Simplification of a dust emission scheme and comparison with data. Journal of Geophysical Research D: Atmospheres. 109(10).
  15. Shi, Y., Zhang, J., Reid, J.S., Hyer, E.J., Hsu, N.C., 2013. Critical evaluation of the MODIS deep Blue aerosol optical depth product for data assimilation over North Africa. Atmospheric Measurement Techniques. 6, 949-969.