Investigation of Atmospheric Pattern and Simulation of the Frontal Sandstorm Emission over Eastern and Southeastern Iran (case study 23 & 24 April 2019)

Document Type: Original Research Paper

Authors

1 Department of Earth Sciences, Islamic Azad University, Science and Research Branch, P.O.Box 14515-775, Tehran, Iran

2 Department of Air Pollution and Atmospheric Chemistry, Atmospheric Science & Meteorogical Research Center, P.O.Box 14965-114, Tehran, Iran

Abstract

The present study simulates the frontal dust storm by means of WRF-Chem model and AFWA emission scheme between April 23 and 24, 2019. It then applies reanalysis data (ERA5) to analyze this case from a synoptic perspective. The simulation results show that the model have been accurately characterized first by the onset of dust from the south-east of the country in Kerman Province and then via its transmission to large areas of the east and south-east. The model output also fits well with satellite images. A quantitative comparison of PM10 concentration of the model with actual values shows that the PM10 model estimates are larger than actual values, though it predicts the trend of concentration changes well. Examining the synoptic maps, the isobars’ curve, wind direction change, and temperature advection in the area reveals the presence of atmospheric fronts within a strong dynamic low-pressure system. This causes high temperature and pressure gradients, in turn speeding up the wind within the region. Results from the synoptic analysis show that by passing the frontal system and behind the cold front, a dust mass is formed, which gradually spreads in eastern and the southeastern regions of Iran. In this case, extreme pressure gradient, cold front passage, low-level jet, wind gust on dry areas of dry Hamoon wetland, and cold air advection over flat area of the Lut Desert are important factors in storm formation and emission, east of the country.

Keywords


Alizadeh Choobari, O., Zawar-Reza, P. and Sturman, A. (2014). The global distribution of mineral dust and its impacts on the climate system: a review. Atmos. Res., 138, 152–165. http://dx.doi.org/10.1016/j.atmosres.2013.11.007.
Asghari, M., et al.
84
Chou, M. D. and Suarez, M. J. (1994). An efficient thermal infrared radiation parameterization for use in general circulation models. NASA Tech. Memo., 104606(3), p. 85.
Colarco, P., da Silva, A., Chin, M. and Diehl, T. (2009). Online simulations of global aerosol distributions in the NASA GEOS-4 model and comparisons to satellite and ground-based aerosol optical depth. J. Geophys. Res., 115, D14207. doi: 10.1029/2009JD012820.
De Longueville, F., Hountondji, Y.-C., Henry, S. and Ozer, P. (2010). What do we know about effects of desert dust on air quality and human health in West Africa compared to other regions? Science of the Total Environment. 409(1), 1-8.
Ginoux, P., Chin, M., Tegen, I., Prospero, J.M., Holben, B., Dubovik, O. and Lin, S.J. (2001). Sources and distributions of dust aerosols simulated with the GOCART model. J. Geophys. Res., 106 (D17), 20255–20273.
Goudie, A. S. (2009). Dust storms: Recent developments. Journal of environmental management, 90(1), 89-94.
Grell, G. A., Peckham, S. E., Schmitz, R., Mckeen, S.A., Frast, G., Skamarock, W. C. and Eder, B. (2005). Fully coupled "online" chemistry within the WRF model. Atmospheric Environment, 39(37), pp.6957-6975.
Grell, G. Freitas, S. R., Stuefer, M. and Fast, J. (2011). Inclusion of biomass burning in WRF-Chem: impact of wildfires on weather forecasts. Atmospheric Chemistry & Physics, 11(11).
Hong, S., Y. and Lim, O. J. (2006). The WRF single-moment microphysics scheme (WSM6). J. Korean Meteor. Soc., 42,129-151.
Iacono, M. J., Delamere, J. S., Mlawer, E. J., Shephard, M. W., Clough, S. A. and Collins, W. D. (2008). Radiative forcing by long-lived greenhouse gases: Calculations with the AER radiative transfer models, J. Geophys. Res., 113, D13103, doi: 10.1029/2008JD009944.
Karami, S., Hossein Hamzeh, N., Ranjbar Saadatabadi, A. and Mousavi, M. (2018). Synoptic study and simulation of soil storm in Khuzestan province in February 2016, Journal of Meteorology and Atmospheric Sciences, 1(2), 177-189.
Kargar, A., Bodaghjamali, J., Ranjbar Saadatabadi, A., Moineddini, M. and Goshtasb, H. (2016). Numerical simulation of sandstorms and heavy dust in eastern Iran using the WRF-Chem model (Case study: May 31 and June 1, 2011), Natural Environment, Natural Resources of Iran, 69 (4), 1077-1089.
Kawamura, R. (1951). Study on sand movement by wind, Rep. Inst. Sci. Technol. Univ. Tokyo, 5(3), 95– 112.
LeGrand, S. L., Polashenski, C., Letcher, T. W., Creighton, G. A., Peckham, S. E. and Cetola, J. D. (2019). The AFWA dust emission scheme for the GOCART aerosol model in WRF-Chem v3.8.1, Geosci. Model Dev., 12, 131–166, https://doi.org/10.5194/gmd-12-131-2019.
Marticorena, B., and Bergametti, G. (1995). Modeling the atmospheric dust cycle: 1. Design of a soil-derived dust emission scheme: Journal of Geophysical Research, 100, 16415–16430, doi: 10.1029/95JD00690.
Mlawer, E. J., Taubman, S. J., Brown, P. D., Iacono, M. J. and Clough, S. A. (1997). Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave. Journal of Geophysical Research: Atmospheres, 102(D14), 16663-16682.
Mitchell, K. (2005). The community Noah land surface model (LSM), User’s Guide, available at: ftp://ftp.emc.ncep.noaa.gov/mmb/ gcp/ldas/noahlsm/ver_2.7.1 (last access: May 2018).
Nakanishi, M. and Niino, H. (2006). An Improved Mellor-Yamada Level 3 Model: Its Numerical Stability and Application to a Regional Prediction of Advection Fog. Boundary-Layer Meteorology, 119, 397-407.
Noh, Y., Cheon, W.G. and Hong, S.Y. (2003). Improvement of the K-profile model for the planetary boundary later based on Large Eddy Simulation Data. Boundary-Layer Meteorology (2003) 107: 401. https://doi.org/10.1023/A:1022146015946.
Prospero, J.M., Ginoux, P., Torres, O., Nicholson, S.E., Gill, T.E. (2002). Environmental characterization of global sources of atmospheric soil dust identified with the NIMBUS 7 Total Ozone Mapping spectrometer (TOMS) absorbing aerosol product. Rev. Geophys. 40 (1), 1002. http://dx.doi.org/ 10.1029/2000RG000095.
Ranjbar Saadatabadi, A., Mihanparast, M., Nouri, F. (2016). Study of dust phenomenon in western Iran from a meteorological perspective (long-term and short-term study), Nivar Scientific and Extension Journal, 92(93), 53-66.
Rashki, A., Kaskaoutis, D.G., Rautenbach, C. J., Eriksson, P. G., Qiang, M. and Gupta, P. (2012). Dust storms and their horizontal dust loading in the Sistan region, Iran. Aeolion Research. 5(1), 51-62.
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85
Shao, Y. (2008). Physics and Modelling of Wind Erosion. Springer Science, New York.
Rezazadeh, M., Irannejad, P. and Shao, Y. (2013). Dust Emission Simulation with WRF-Chem Numerical Weather Prediction Model and Using New Surface Data in the Middle East: Journal of Earth and Space Physics: 39 (11), 191-212.
Squires, V.R. (2007). Dust and sandstorms: an early warning of impending disaster, P 15-25. In: Youlin, Y., V. Squires and L. Qi (Eds.), Global Alarm: Dust and Sand Storms from the World’s Drylands. United Nations.
Tanaka, T. Y. and Chiba, M. (2006). A numerical study of the contributions of dust source regions to the global dust budget. Global and Planetary Change, 52(1), 88-104.
Tegen, I., Werner, M., Harrison, S. and Kohfeld, K. (2004). Relative importance of climate and land use in determining present and future global soil dust emission: Geophysical Research Letters, 31, L05105.
Thompson, G., Field, P. R., Rasmussen, R. M. and Hall, W., D. (2008). Explicit Forecasts of Winter Precipitation Using an Improved Bulk Microphysics Scheme. Part II: Implementation of a New Snow Parameterization. Mon. Wea. Rev. 136 (12): 5095–5115. https://doi.org/10.1175/2008MWR2387.1
Wang, W., Bruyère, C., Duda, M., Dudhia, J., Gill, D., Michael, K., Keene, K., Chen, M., Lin, H. C., Michalakes, J., Rizvi, S., Zhang, X., Berner, J., Soyoung, H. and Fossell, K. (2017). Guide for the Advanced Research WRF (ARW) Modeling System Version 3.9, NCAR technical note, Mesoscale and Microscale Meteorology Division, National Center for Atmospheric Research, Boulder, Colorado, USA.
Westphal, D.L., Toon, O.B. and Carlson, T.N. (1988). A case study of mobilization and transport of Saharan dust. Journal of the Atmospheric Sciences, 45(15), 2145-2175.
Westphal, D.L., Toon, O.B. and Carlson, T.N. (1987). A two‐dimensional numerical investigation of the dynamics and microphysics of Saharan dust storms. Journal of Geophysical Research: Atmospheres, 92(D3), 3027-3049.
Zakey, S., Solmon, F. and Giorgi, F. (2006). Implementation and testing of a desert dust module in a regional climate model, Atmos. Chem. Phys., 6, 4687–4704.