Modeling and Analysis of Dust Storms of Yazd Province Using Numerical Models

Message:
Abstract:
Introduction
One of the factors that affect the climate of arid and semi-arid areas is dust storm. Numerical models are new methods for evaluation of dust storms which can also be used for forecasting dust storms. Weather patterns that lead to dust outbreaks can be simulated using computer models that support a wide range of simulations related to the long-range transport, dispersion, and deposition of aerosols. Mesoscale atmospheric models are widely used to capture the complex flow and meteorological parameters essential in dust outbreaks (for example, Ginoux et al, 2001; Zender et al, 2003; Kim, 2008).But one of the main problems in the study of contaminates such as dust is to quantify the relationship between air quality and pollution sources. Identify the source of infection is the first step in the process of determining an effective strategy for controlling pollution. One way to find the sources of pollution is back trajectory this means that the back trajectories from the receiver site can be used to specify the source location (Petzold et. al. 2009). Today, a coupling of meteorological and trajectory models are common methods in studies of dust storms. Yazd province is one of the low rainfall areas in the center of Iran that is almost covered with desert and sandy plains. Consequently, this province is frequently faced with dust storm phenomena. In this study, owing to lack of numerical studies of dust storm in Iran, dust storms of Yazd province were analyzed using numerical models. We used two numerical models, Weather Research and Forecasting (WRF) model and HYbrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model. WRF model analyses were used to investigate meteorological conditions in the center of Iran and HYSPLIT back-trajectory analyses were used to investigate the wind patterns that led to dust outbreaks by evaluating air transport pathways reaching Yazd area during dusty days. Study area: Yazd Province is one of the 31 provinces of Iran. It is in the center of the country. The province of Yazd has one of the driest climates in Iran due to its location east of the Zagros Mountains. Yazd is the driest major province in Iran, with an average annual rainfall of only 60 millimeters (2.4 in), and also the hottest north of the Persian Gulf coast, with summer temperatures very frequently above 40 °C (104 °F) in blazing sunshine with no humidity. Due to this climate and geographical position, the province of Yazd have been subjected to dust storm phenomena and have been suffering from large damages.
Materials And Methods
In this study numerical models are used to investigate and forecast of dust storms. At first, Dust storms in the period of 2000-2009 were studied and dust storms which reduced visibility to less than 1000 meters were extracted. Then one of the strongest dust storms on 29 May 2003 was analyzed in detail. The Advanced Research version of WRF (ARW) was used to produce atmospheric fields at a high resolution over the study region. HYSPLIT model was used to compute simple air parcel trajectories as well as dispersion and deposition simulations. 2 nested domains of 45 and 15 km horizontal resolutions and 28 vertical levels was defined in WRF model that first domain was used for synoptic analysis and second domain was used for analysis of convergence zones and convective motions in the center of Iran. The model was integrated continuously for 48 h starting from 00UTC of 28 May 2009. Initial and boundary conditions were adopted from National Centers for Environmental Prediction Final Analyses (NCEP FNL) data available at 1° horizontal resolution. Boundary conditions were updated at 6-h intervals during the period of model integration. Then WRF outputs converted to format of input data for HYSPLIT model and this model was run to investigate the source of dust storm using calculation of back trajectories from receptor site. The back trajectories provide the Lagrangian path of the air parcels in the chosen time scale, which will be useful to identify the source locations of the pollutant that fall in the track of the back trajectories. Also for reduce uncertainty of back trajectories, trajectories were calculated at different altitudes (10 m, 500 m and 1000 m).
Results And Discussion
Results of this study indicated that 20 dusty dates with visibility less than 1000 meter were occurred in Yazd station. Most of these cases occurred in February to July and in most of these cases wind direction were west and northwest. Synoptic and dynamic analysis of dust storm on 29 May 2003 using WRF outputs shows that passing of cyclonic systems of high levels and surface heating create strong instability and high surface wind speed in the region that this higher surface wind speeds lead up dust and sand. These conditions are associated with deep mixed layers and convective conditions before storm and a maximum area of strong convergence of surface wind at the time of starting dust storm and dust storm has formed. Back trajectory analysis using HYSPLIT model indicated that Gavkhoni marsh in southern part of Isfahan province and arid lands around it are the sources of the considered dust storm.
Conclusion
In this study it was shown that the use of numerical models and appropriate approach to assess and predict dust storms. The models were used in this study were Weather Research and Forecasting (WRF) model and HYSPLIT trajectory model. For the case that investigate in this study WRF model simulated the wind flow under the influence of an existing cyclonic system during the study period. The passage of the cyclone with cold air in the central regions of Iran simultaneously with the heating surface area has created severe instability and formed the dust storm. Further, the back trajectories obtained from HYSPLIT model predict winds come in the quadrant between north and west where the Gavkhoni dry salt marsh is located.
Language:
Persian
Published:
Journal of Geography and Environmental Hazards, Volume:3 Issue: 12, 2015
Pages:
67 to 83
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