Dust tracking and modeling in Southeast of Iran (Case study: Dust storm from December 16 to 20, 2016)

doi:10.21203/rs.3.rs-3920082/v1

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Dust tracking and modeling in Southeast of Iran (Case study: Dust storm from December 16 to 20, 2016)

https://doi.org/10.21203/rs.3.rs-3920082/v1

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Blowing dust is one of the most common natural phenomena in arid and semi-arid regions, which causes a lot of damage every time it occurs. This phenomenon is introduced as a natural hazard in terms of negative effects in natural and human-managed ecosystems, and it is one of the most important problems of ocieties in arid and semi-arid regions. In this research, in order to investigate and analyze this phenomenon, it was simulated by the WRF-Chem model, and MODIS satellite data and the HYSPLIT model were also used to investigate the mechanism of particle transport and its routing in the Jazmurian basin in the southeast of Iran. The results showed that the aerosol optical depth index is high in eastern Iran on December 16 to 20, and the particles originating from this part were mainly affected by the northern currents and moved to the south. Also, the results of the numerical simulation of the dust storm using the WRF-Chem model showed that the surface concentration values of the output particles of the WRF_Chem model at UTC18 on December 17, 2016 in the south of Sistan and Baluchistan province and Hormozgan province were higher than 2500 micrograms per cubic meter. and in the central areas of Jazmurian region, the concentration of dust reaches more than 2000 micrograms per cubic meter.

Numerical simulation

dust storm

WRF-Chem

MODIS satellite data

Jazmurian

December 16–20

2016 storm

Today, the phenomenon of dust is one of the basic problems of arid and semi-arid regions, whose originating in source areas such as dry wetlands and rivers. Dust, by affecting the human respiratory system, causes sometimes irreparable damage to health. The intensity and frequency of this phenomenon is increasing, which is closely related to climate change, as well as to changes in land cover and land use. Climate change includes global warming and changes in parameters such as precipitation and wind speed. For example. the change in temperature gradient between the equator and the pole, will lead to a change in wind speed. Undoubtedly, this change will affect the intensity and frequency of wind erosion and dust storms. The combination of the phenomenon of climate change with human activities increases soil degradation, wind erosion and desertification, and the continuation of this process causes the loss of soil organic carbon and causes the intensification of dust storms (Sun et al. (20) ). It should also be kept in mind that climatic parameters have a great influence on many other indicators used in wind erosion models, including soil type (Matin Far and Maleki (10)) and vegetation cover (Bayat Mohed) (3). Climatic factors, particualrly the presence of erosive wind, can increase erosion on surfaces sensitive to wind erosion (Kalt et al. 5). Also, climate forecasts show that the increase in droughts as a result of climate change has caused a decrease in vegetation and soil moisture, which favors wind erosion in the affected areas (Blanka et al. 4, Mesoosi et al. 11). As mentioned, the phenomenon of wind erosion occurs parallel to the dryness of the environment and the progress of desertification processes, which can be the result of global warming and climate change. The main sources of dust in Southwest Asia include the Sistan Basin on the border between Iran and Afghanistan, the Makran Plain along the coast of the Oman Sea, the plains of Pakistan to the northwest of India, and the Indian Basin (Alizadeh et al. 2). Iran is subject to sudt from many of these source regions, notably the Sistan Plain with an area of 15197 square kilometers (Nuri et al. 15, Heydari Mekarim et al. 7) in the east of Iran with unfavorable and dry climate and suitable conditions for wind erosion and hill movement sand and the occurrence of dust storms (Framers 6). The maximum dust emission of Sistan region in eastern Iran and southwestern Afghanistan and Pakistan occurred in the summer season and these storms load dust from local to regional scale (Rashki et al. 16). Therefore, finding the origin and predicting the dust phenomenon is of great importance. In order to achieve dust forecasts with high accuracy, the phenomenon must first be modeled. The modeling of atmospheric phenomena, including dust lofting and transport, is a very complex process due to its dynamic nature and the involvement of various factors. Weather models with different goals have been designed in the past to model these phenomena, but one of the most important disadvantages of these models is their limitation and not taking into account all the effective factors, which sometimes causes the accuracy of the results to decrease. The output of these models is atmospheric quantities and parameters, which alone are not capable of simulating and predicting quantities such as the concentration of suspended particles, air pollution, floods, sea waves, and to simulate such quantities, these models must be combined with other models such as for atmospheric pollutants, dust, etc. Such composite models can simulate and predict many cases of dust storms. The Numerical Weather Forecasting Model (WRF) is a new generation numerical weather forecasting system designed for research and operational atmospheric forecasting applications. WRF is the basis of the hybrid modeling system WRF-Chem, which can predict the concentration of suspended particles and air quality, which is created by combining a numerical weather model (WRF) and a pollutant sector model. Various studies including Naboi et al. (14,13), Su and Fang (19), Xialen and Hong Sheng (23), Reza et al. 17, Song et al. 18, Jiu et al. (8), Kim et al. (9) ), Mankhestseg et al. (12), Takseria et al. (22), Song et al. (20), Tang et al. (21) have been carried out with the WRF-Chem model on climate phenomena, especially dust and environmental pollutants. The purpose of this research is to simulate the dust storm of December 16–20, 2016 using composite models on the Jazmurian basin. This is very important because dust is a qualitative phenomenon and it is not possible to manage it with qualitative values, but simulating it makes numerical values and better manage it and reduce its harmful effects based on numerical values. It is possible to determine the origins and peak times as well as the direction of dust movement.

2.1 Study Area

Jazmurian is an endorheic basin located in the provinces of Kerman, Sistan and Baluchistan with the coordinates of latitude 26 33 to 29 36 N and longitude 16 56 to 26 61 E and an area of 69374 square kilometers. The average annual rainfall of this basin is about 172 mm. The height of the highest point of this range is 4359 meters and the lowest point is 354 meters above sea level (Ahmadi et al. 1). Its lowest point is covered by a seasonal lake. In general, the formations of the studied area are from the Cenozoic era, with a lot of formations from the Quaternary and Tertiary periods. The main land uses include poor pastures and barren lands. It has dried out further in recent decades due to climate change, agricultural exploitation, and water diversion. The geographical location of the studied area is shown in Fig. 1.

2.2 Method

In this research, Aqua Modis satellite images were used for December 19, 2016 to visualize the dust storm and HYSPLIT software was also used to understand the transport route of dust particles.

2.2.1 Dust storm routing using HYSPLIT model

The HYSPLIT model was designed by Draxler and Hess in 1997 and has been improved over the past few decades. This model is actually a dual model for dust movement calculations, dispersion and simulation of particle deposition using puff and particle approaches. This model is used to simulate the dust trajectory and identify the origin areas as well as the areas affected by the dust storm. The calculation method of the model is a combination of Eulerian and Lagrangian perspectives, and for this reason HYSPLIT is called a dual model. In order to determine the path of dust movement by this model, gridded meteorological data is needed. The minimum data required to analyze the movement path of dust is the orbital and meridional component of the wind, the vertical velocity (omega) and the geopotential height in a reference level. Several types of data are used for the input of the model, which in the study area is the only possibility to use GDAS data. GDAS is a global data set with two grids, one grid with a resolution of 1 degree and the other with a resolution of 0.5 degrees and are available for every three hours. GDAS data are available at 1° resolution since 2006 and 0.5° resolution since September 2007. Using data with a lower resolution will make the output of the model more accurate(challa et al 2008).

2.2.2 Characterization of dust storm using remote sensing

One of the ways to detect and identify the phenomenon of dust is remote sensing technology, and based on this technology, it is possible to help identify the sources of production and the path of fine dust (Bacon, 2010), it was observed through previous studies that Modis images have a high ability to detect It has dust, and in most cases, the index was used to detect fine dust, and the main reason is that the images related to the Madis sensor, in addition to highlighting the dust, have many spectral bands and have a suitable time step. Further, using MODIS satellite images and remote sensing methods, the dust in the studied area was revealed. MODIS data was downloaded from https://search.earthdata.nasa.gov/search/granules.

2.2.3 WRF-Chem

Next, in order to simulate the numerical forecasting and research model of weather conditions with chemistry (WRF-Chem), as included in Version 3 of the WRF model, which is a research and operational model for simulating and predicting the concentration of air pollutants in the atmosphere caused by natural mechanisms and human activities. (pollutants) and dust in different sizes, the way they spread and deposit. The WRF-Chem model has diverse applications such as numerical weather forecasting, data evaluation studies, physical parameterization research, climate simulation, air pollution modeling and coupled ocean-atmosphere system and its modular structure that makes the model flexible to different input data and change. be in the nature of modules. The WRF-Chem model has more advanced numerical capabilities than other models, and due to its higher resolution, it examines local effects more accurately Unlike most similar models, the WRF-Chem pollutant chemistry and transport model dis coupled with an atmospheric model and calculates its required atmospheric quantities online (including their interaction with pollutants such as dust), so in addition to the quantities related to atmospheric chemistry, atmospheric quantities such as wind at the surface It also provides pressure and geopotential height as output of the model. The structure of the WRF-Chem model is shown in Figure (2).

WRF-Chem model configuration

In this research, version 3.9.1 of WRF-Chem model was used for the numerical simulation of dust storms. Boundary and initial conditions are obtained from GFS (NOAA) with a horizontal resolution of 1°*1°. Static geographic data such as height of roughness, soil characteristics, fraction of vegetation and land use were used from USGS data. Table 1 shows the schematics used in the implementation of the WRF-Chem model.

Table 1

of schemas used in the implementation of the WRF-Chem model
WRF Single-Moment 5-class	Microscale physics
RRTM (Mlawer, 1997)	long wave radiation
Goddard shortwave(Chou, 1998)	short wave radiation
Noah Land Surface Model (Chen,1996)	Surface physics
YSU(Noh et al., 2002)	boundary layer
Grell 3D (Grell,1993)	convection

The true color image and aerosol optical depth of the MODIS sensor of the Aqua satellite on December 19, 2016 are shown in Fig. 3. The amount of AOD in the southeast region of Iran is high and it is also clear in the true color image of the dust mass over the Jazmurian region.

The output of the HYSPLIT model in the forward method for December 16, 2016 at 12 UTC, which is shown in the form of a matrix with GDAS data with a horizontal resolution of 0.5 degrees with the Forward method for 24 hours at an altitude of 100 meters, is shown in Fig. 4. The particles originating from this section mainly moved south from source areas further north.

Figure 5- shows the optical depth values of WRF-Chem model output particles at 12 UTC on December 17, 2016. The AOD values over the south of Sistan and Baluchistan province and the border between Afghanistan and Pakistan, west of the Oman Sea and east of the Persian Gulf show a significant increase compared to the previous figure. Also, the amount of this quantity has increased for the Jazmurian region and has reached 0.8 in some areas. The optical depth of particles on a large part of Jazmurian region is more than 0.5.

Figure 17 shows the surface concentration values of WRF_Chem model output particles at 12 UTC on December 17, 2016. The surface dust concentration in the south of Sistan and Baluchistan province and Hormozgan province is higher than 1600 micrograms per cubic meter, and in the eastern areas of Jazmurian region, the dust concentration is higher than 1200 micrograms per cubic meter.

Figure 18 shows the surface concentration values of WRF_Chem model output at UTC18 on December 17, 2016. The surface dust concentration in the south of Sistan and Baluchistan province and Hormozgan province is higher than 2500 micrograms per cubic meter, and in the central areas of Jazmurian region, the dust concentration is higher than 2000 micrograms per cubic meter. The concentration of dust shows a significant increase compared to 6 hours ago.

Figure 19 shows the surface concentration values of WRF_Chem model output at UTC00 on December 18, 2016. The surface dust concentration in the south of Sistan and Baluchistan province and Hormozgan province is still higher than 2500 micrograms per cubic meter, and in the central areas of Jazmurian region, the dust concentration is simulated to be higher than 1400 micrograms per cubic meter, which is a decrease compared to the previous figure. has been found.

Figure 20 shows the surface concentration values of WRF_Chem model output particles at UTC06 on December 18, 2016. The expansion of the area with a surface dust concentration higher than 2500 micrograms per cubic meter has decreased in the south of Sistan and Baluchistan province and Hormozgan province, and in the central areas of Jazmurian region, the dust concentration is simulated higher than 1000 micrograms per cubic meter, which is compared to the previous figure. It has decreased drastically in Jazmurian region.

Figure 21 shows the surface concentration values of WRF_Chem model output at UTC12 on December 18, 2016. The surface dust concentration has been greatly reduced in the south of Sistan and Baluchistan province and Hormozgan province, and except for the southern areas of Jazmurian region where the dust concentration between 600 and 800 micrograms per cubic meter has been simulated, surface dust is not observed in other areas of this region.

Figure 22 shows the surface concentration values of WRF_Chem model output particles at UTC18 on December 18, 2016. The surface dust concentration is higher in the south of Sistan and Baluchistan province and Hormozgan province compared to the previous figure. Also, in most of the southern half of Jazmurian region, the concentration of dust has exceeded 2500 micrograms per cubic meter.

Figure 23 shows the surface concentration values of WRF_Chem model output at UTC00 on December 19, 2016. The surface dust concentration has increased in the south of Sistan and Baluchistan province and Hormozgan province compared to 6 hours ago. Also, the surface concentration of dust has increased in most of the central and southern areas of Jazmurian region.

Figure 24 shows the surface concentration values of WRF_Chem model output at UTC06 on December 19, 2016. The surface concentration of higher dust in the south of Sistan and Baluchistan province and Hormozgan province has decreased in some places compared to 6 hours ago. Also, the surface concentration of dust in most of the central and southern areas of Jazmurian region is greatly reduced.

Figure 25 shows the surface concentration values of WRF_Chem model output particles at 12 UTC on December 19, 2016. The surface dust concentration is higher in the south of Sistan and Baluchistan province, Hormozgan province and Jazmurian region has decreased sharply. The surface concentration of dust in the southern half of Jazmurian region has reached below 1000 micrograms per cubic meter.

Figure 26 shows the surface concentration values of WRF_Chem model output particles at UTC18 on December 19, 2016. The surface dust concentration is higher in the south of Sistan and Baluchistan province, Hormozgan province and Jazmurian region has decreased sharply. The surface concentration of dust in the southern half of Jazmurian region has reached below 1000 micrograms per cubic meter.

Figure 27 shows the surface concentration values of WRF_Chem model output at UTC00 on December 20, 2016. The surface concentration of higher dust in the south of Sistan and Baluchistan province, Hormozgan province has increased sharply and has reached more than 2000 micrograms per cubic meter. The surface concentration of dust in the southern half of Jazmurian region is often between 1400 and 1600 micrograms per cubic meter.

Figure 28 shows the surface concentration values of WRF_Chem model output at UTC06 on December 20, 2016. The surface concentration of dust is higher in the south of Sistan and Baluchistan province, Hormozgan province and the Oman Sea above 2000 micrograms per cubic meter. The surface concentration of dust in the southern half of Jazmurian region has decreased and is between 1200 and 1300 micrograms per cubic meter.

Simultaneous use of satellite data with remote sensing technology and hybrid models is very valuable in dust simulation. In this research, MODIS satellite data was used, the results of which showed that the AOD level is high in the southeastern region of Iran during the case study period, and also the dust mass on the Jazmurian region is clearly visible in the true color imagery. Also, the HYSPLIT model was used for the transmission and routing of dust particles, the results of which showed that the particles originating from this section were mainly affected by the northern currents and moved towards the south. In the last step, the WRF-Chem hybrid model was used to simulate the dust storm, which numerically simulated the AOD value as well as the surface concentration of dust particles. The results showed that the AOD values on the south of Sistan and Baluchistan province and the border between Afghanistan and Pakistan, west of the Oman Sea and east of the Persian Gulf show a significant increase compared to before. Also, the amount of this quantity has increased for the Jazmurian region and has reached 0.8 in some areas. The optical depth of particles on a large part of Jazmurian region is more than 0.5. Also, the surface concentration values of the output particles of the WRF_Chem model were simulated at different hours of the incident. The surface concentration of dust is higher in some hours, such as in the south of Sistan and Baluchistan province, Hormozgan province and Oman Sea, it is higher than 2000 micrograms per cubic meter. For example, the values of the surface concentration of particles output from the WRF_Chem model at UTC18 on December 17, 2016 show that the surface concentration of dust in the south of Sistan and Baluchistan province and Hormozgan province is higher than 2500 micrograms per cubic meter, and in the central areas of Jazmurian region, the dust concentration is higher than 2000 µg/m3 is simulated. Also, the surface concentration values of WRF_Chem model output particles at 18:00 UTC on December 18, 2016, in most of the southern half of Jazmurian region, the dust concentration has exceeded 2500 micrograms per cubic meter.

Using the WRF-Chem model, as well as satellite data and the HYSPLYT model, the dust storm was simulated from December 16 to 20, 2016. Numerical prediction and simulation of dust can help in locating the origin of dust in the region. Also, it is very important to determine the peak hours of dust and the movement path of particles. In general, there are two sources of dust, internal sources and external sources. By simulating the dust storm of foreign origins, it is also determined that in this research, dust centers in the east, southeast and south of Iran, which are the countries of Afghanistan (Hamon plain) and the Arabian deserts in the south, are active. Therefore, many dusts in the Jazmurian area can become more intense if the direction of the wind is from the east or from the south. In other words, the Jazmurian basin is the source of dust in southern Iran during droughts, and if this phenomenon is activated when the external foci (Hirmand plain in Afghanistan and Arabian deserts) are activated because they are in the path of Iran's winds, the intensity of this phenomenon will increase. increase The necessity to prevent it requires international protocols for the correction and restoration of degraded lands, the release of water and watershed management and desertification activities in order to stabilize the degraded soil levels.

-Ethics approval and consent to participate: We, the authors, declare ethical approval and consent to participate in this paper.

-Consent for publication : We, give my consent for the publication of identifiable details, which can include photograph(s) and/or videos and/or case history and/or details within the text (“Material”) to be published in the above Journal and Article.

-Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

-Author contributions (Please ensure that all authors are individually mentioned in the author contribution statement.): F.S.S. and N.K. conceived of the presented idea, developed the theory and performed the computations. N.K. Writing—Review and Editing. All authors discussed the results and contributed to the final manuscript.

-Funding: no Funding

-Availability of data and materials: Data are available .The data that support the findings of this study are available from the corresponding author upon reasonable request.

Ahmadi, H.; Moradi, A.; Ismailpour, Y.; & H. Gholami, 2019. Evaluation of land sensitivity to desertification using the system dynamics approach in Jazmourian watershed, Journal of Water and Soil Conservation Research, 26(2), 211-224
Alizadeh Choobari, Omid, Zawar-Reza, Peyman and Sturman, Andrew. 2012. “Atmospheric for city of the three-dimensional distribution of dust particles over Australia: A case study”, Journal of Geophysical Research, 117 Vols., No. D11206, pp. 1-19.
Bayatmovahed, F., 2011. The status of vegetation in wind erosion control.1st edition, Iran Agricultural Science Press publication, 276 p.
Blanka, V., Mezõsi, G., and Meyer, B. 2013. Projected changes in the drought hazard in Hungary due to climate change, Idõjárás: Quarterly Journal Hungarian Meteorol. 117: 219-237.
Callot, Y., Marticorena, B., and Bergametti, G. 2000. Geomorphologic approach for modelling the surface features of arid environments in a model of dust emissions: application to the Sahara desert. Journal Geodinamica. Acta. 13: 5. 245-270.
Challa, V., J. Indrcanti, and J. Baham. (2008). Sensitivity of Atmospheric Dispersion Simulations by HYSPLIT to the Meteorological Predictions from a Meso Scale Model. Environmental Fluid Mechanics. 8(4), 367-387.
Draxler, R.R. and Hess, G.D. (1997) Description of the HYSPLIT-4 Modeling System. NOAA Technical Memorandum ERL ARL-224, NOAA Air Resources Laboratory, Silver Spring, 1-24.
Farmarez, Morteza. 2011. "Investigation of the genetic and mineralogy of the constituent elements of sand dunes (east of Sistan plain)", Proceedings of the National Conference on Wind Erosion and Dust Storms, Yazd-Iran, 27-28 Jun, Volume 2, p. 129-138 (In Persion).
Heydari Mokarar, Hamid., Sadegh Beigi, Nasreen. And poodinepir, Hadi. 2013. "Evaluation and analysis of crises resulting from dust storms on Lake Hamon", National Conference on Protection of Wetlands and Aquatic Ecosystems, Iran, 19 Mey. Volume 1, p. 1-10(In Persion).
Ju, T. Li, X. Zhang, H. Cai, X. Song, Y. 2018. Comparison of two different dust emission mechanisms over the Horqin Sandy Land area: Aerosols contribution and size distributions. Atmospheric Environment. 176 (2018) 82–90
Kim, D. Chin, M. Kemp, E. Tao, Z. Peters-lidard, C. Ginoux, P. 2017. Development of high-resolution dynamic dust source function - A case study with a strong dust storm in a regional model. Atmospheric Environment 159 (2017) 11-25
Matinfar, H. R & A. Maleki, 2011.1St edition. Soil Science. Lorestan university press. 312 p.
Mezõsi, G., Meyer, B.C., Loibl, W., Aubrecht, C., Csorba P., and Bata, T. 2013. Assessment of regional climate change impacts on Hungarian landscapes. Journal Region. Environ. Change. 13: 797-811.
Munkhtsetseg, E. Shinoda, M. Gillies, J. Kimura, R. King, J. Nikolich, G. 2016. Relationships between soil moisture and dust emissions in a bare sandy soil of Mongolia. Particuology 28 (2016) 131–137
Nabavi, S. Haimberger, L. Samimi C, 2017. Sensitivity of WRF-chem predictions to dust source function specification in West Asia. Aeolian Research. 24(2017) 115-131
Nabavi, S. Haimberger, L. Samimi C,.2016. Climatology of dust distribution over West Asia from homogenized remote sensing data. Aeolian Research 21(2016) 93-107.
Nouri, Soheila, Shahriari, Alireza, Mirtahari, Mohammad, Abedinzadeh, Kazem. and Sadat Fatemi, Samira. 2011. "The role of groundwater table fluctuations in the intensification of wind and dust erosion", Proceedings of the National Conference on Wind Erosion and Dust Storms, Yazd-Iran, 27-28 Jun, Volume 2, p. 81-90(In Persion).
Rashki, Alireza, Kaskaoutis, Dimitris, Rautenbach, C.J.Dew and Eriksson, Patrick. 2012. “Changes of Permanent Lake Surface, and Their Consequences for Dust Aerosol and Air Quality: The Hamoun Lakes of the Sistan Area, Iran”, Journal of Atmospheric Aerosol-Regional Characteristics-Chemistry and Physics, Chapter 6, pp. 163-202, Website: http://dx.doi.org/10.5772/48776.
Rizza, U. Miglietta, M. Mangiaa, C. Lelpo, P. Morichetti, M. Iachini, C. Vigili, S. Passerini, G. 2018. Sensitivity of WRF-Chem model to land surface schemes: Assessment in a severe dust outbreak episode in the Central Mediterranean (Apulia Region). Atmospheric Research. 201 (2018) 168-180.
Song, Z., Wang, J., and Wang, S. 2007. Quantitative classification of northeast Asian Dust events. Journal of Geophysical Research, 12(D4). doi:1029/2006JD007048
Su, L. Fung , C.H.J. 2015. Sensitivities of WRF-Chem to dust emission schemes and land surface properties in simulating dust cycles during springtime over East Asia. Journal of Geophysical Research: Atmospheres. No 11. Pp 215-230. 10.1002/2015JD023446
Sun, J.H., Zhao, L.N., Zhao, S.X. 2003a. An integrated modeling system of dust storm suitable to North China and Applications. Clim Environ. 8. 125–142.
Tang,Y. Han, Y. Liu, Z. 2018. Temporal and spatial characteristics of dust devils and their contribution to the aerosol budget in East Asia—An analysis using a new parameterization scheme for dust devils. Atmospheric Environment Volume 182, June 2018, Pages 225-233
Teixeira, J.C. Carvalho, A.C. Tuccella, P. Curci, G. Rocha, A. 2016. WRF-chem sensitivity to vertical resolution during a Saharan dust event. Physics and Chemistry of the Earth 94 (2016) 188-195
Xiaolan, L. Hongsheng, Z. 2014. Soil Moisture Effects on Sand Saltation and Dust Emission Observed over the Horqin Sandy Land Area in China. JOURNAL OF METEOROLOGICAL RESEARCH. Vol 28.pp 444-452

No competing interests reported.

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Dust tracking and modeling in Southeast of Iran (Case study: Dust storm from December 16 to 20, 2016)

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Abstract

Figures

1. Introduction

2. Materials and Methods

2.1 Study Area

2.2 Method

2.2.1 Dust storm routing using HYSPLIT model

2.2.2 Characterization of dust storm using remote sensing

2.2.3 WRF-Chem

3. Results

4. Discussion

5. Conclusions

Declarations

References

Additional Declarations

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