Wind erosion and generation of dust is one of the most important problems in the Yazd province. To control this phenomenon and overcome the damages a lot of investment has been done for the implementation of many successful and unsuccessful projects across this province. Analysis of erosive winds and estimation of the Resultant Drift Direction (RDD) of sand flow is the fundamental study by which can lead to a more successful implementation of projects, to control wind erosion. In this study, by taking advantages of WIND-ROSE, Storm-rose and Sand-rose has been analyzed wind speed, wind direction and calculation of wind drift potential (DP) to represent a landscape of wind erosion in the Yazd province and with the results of these analysis, the Resultant Drift Direction (RDD) of sand flow and dust be estimated. The results showed that most of the erosive winds in the Yazd province occur in the spring and summer and the lowest erosion occurs in autumn. The results as well revealed that the average percentage of erosive winds which are capable of producing dust are between 6. 4%, in Yazd city, and 23. 6%, in Herat city, and on average, in 44 days there is the possibility of dust in the Yazd province. Therefore, although the prevalence of erosive winds with speed more than 6 meter per second generally does not exceed 14% but, it has the most important role in the occurrence of the wind erosion and dust generation in the Yazd province and the mobility of a large amount of dust is generally from the southwest and west to the north east and east.

Sand dunes developed in 15 provinces with an area of 4. 4 million hectares and 56 Citadel, are one of the most important geomorphological features in Iran. Sand and desert stabilization technical office studies, according to project results identify focal and present four regions including Ahvaz, Dasht-e-Azadegan, Susa and the Omidiyeh in Khuzestan province. The mentioned area includes 279, 505 hectares of land in Khuzestan. This study has used remote sensing technology, GIS techniques and analyzed effective recorded winds data. Toward were reviewed and analyzed the wind regime of the area for direction of source area using Windrose Diagrams. In this study, based on utilizing and composing of image processing techniques such as image enhancement, threshold, false color composition, filtering and analysis and results of wind data analysis, with other investigations is useful to find the source of sand dunes. The results from direction of source area confirm that source of sand dune located in NW to W, notice Windrose in Khuzestan. The source area are flood alluvial fan plain, alluvial fan, agriculture land, meandering rivers and sensitive formation to erosion including Aghajari formation and Bakhtiari formation that located in the in NW to W section.

1-Interoduction: Air pollution has been considered as one of the global challenges. According to world health organization (WHO), dust particles are the 5th most dangerous cause of death 4. 2 million in the world. According to the world meteorological organization (WMO), when the wind speed increases more than 15 m/s and the visibility decreases because of dust particles less than 1 km, it is called a dust storm. Considering the potential impact of dusts around the city of Qom, it is possible to influence the impact of dust storms on the extent of these centers and their contribution to the air quality of the city of Qom in the aftermath of a storm of dust. The dust storms that affect Qom are originated from two local and transitional emission sources. The main objectives of this study were identification of the main quaternary geological structures as emission sources of dust storms, study dust storms paths and determine the important emission sources that are affect Qom air quality. 2-Material and methods: Initially, dust storms were detected using dust codes and verification of MODIS images during the period 2008 to 2017. Remote sensing is a suitable method for detecting dustborne events and has recently been successfully used to understand the location of dust sources. The position of geological formations at the site of the focal points indicates that the bed of most of the focal points is from quaternary deposits. The Quaternary geological period is the fourth and final period of geology, and most of the constituent parts of these centers, including the ancient coniferous terraces and clay alluvial tundra, are prone to dust production. This study were trajectory using HYSPLIT model and orientation index (windrose, dust rose and CPF). In order to investigate the wind condition as one of the most important factors in dust storms, windrose and dust rose were used using WRPLOT software. One of the common ways to identify the geographic direction of dust sources is the CPF function. The CPF examines the potential of any direction in the transfer of pollutants, especially particulate matter released from a source in which the wind is greater than the specified threshold. The HYSPLIT model is one of the most practical methods for determining the duct movement, dispersion and dip galvanizing simulationThe model of the propagation algorithm was identified for each occurrence and was investigated at three altitudes of 10, 500 and 1000 m in backward for 24 hours for local Events and 72 hours for transitional Events. 3-Results and discussion: Out of 531 identified events, after verification by dust codes and MODIS images, 400 events were detected in Qom between 2008 and 2017 years about 84 percent of the incidents occurred in the spring and summer. The results of windrose and dust rose indicate that east and west directions have the highest wind direction in Qom, which are differents in different seasons, and the results of windrose are more similar to the seasonal results of summer and spring, the occurrence of most events in two seasons spring and Summer shows. Seasonal CPF results with slightly different windrose and dust rose results, show the northwest and east directions in the spring and summer, and northwest in the autumn and winter seasons. Due Because of the CPF shows the potential for dust production and most of the events occurred in the spring and summer season, the results of the windrose spring and summer and dust rose were similar and confirm the occurrence of this dust numbers in the two seasons of spring and summer In these directions. The results of HYSPLIT At three altitudes of 10, 500 and 1000 meters in the period from 2008 to 2017 in Qom Due Because of the two altitudes of 1000 and 500 meters are far away from the phenomena and topographic changes of the Earth, they have little effect on the dusts. Dust routing results at 10 m elevation were studied. The results of trajectiries the HYSPLIT model at 10 m elevation in the study period in Qom show that the most important directions of dust entering the city of Qom, Like the results of wind rose, dust rose and CPF, it is east, southeast, west, and southwest, who There are many events in the east and south-east of the west and southwest, and From these directions, there is no significant dusting in the southwest direction around the city of Qom, and in other directions there are many dusty centers. Investigating the frequency and direction of the dust storm trajectory occurring in Qom during the studied period shows that the most important centers dust that affect the air quality of Qom city, where the threat of more events has passed, Respectively, the centers of numbers 4, 10, 11 and 2 are located among these centers, centers numbers 4, 10 and 11 in the direction of east and south-east of the city of QomThe center number 2 is located west of the city of Qom, and this direction was also Is important recognized by the results of wind rose, dust rose and CPF. Also, the results of the HYSPLIT model trajectory for transitional dusts Which has influenced the city of Qom during the studied period, shows that most of these dusts from the country are than Iraq, then Syria and Saudi Arabia. 4-Conclusion: There are several dusts centers around the city of Qom. Among these centers, the center of number 4 (the distance between salt lake and Houz-e-Sultan), located east of Qom, is due to the close distance, high area, the genus of the formation and, most importantly, the abundance The passage of events from this center, which includes the largest number, and centers of numbers 10, 11 and 2 too After the center of number 4, is the most important and most influential source of dust on the city of Qom relative to other centers.

Prevention of sediment movement in the taking area is a fundamental basic task. For source studying of Rafsanjan eolian sediments, step by step method (Ekhtesasi-Ahmadi et al.) was employed. This study is carried out in two stages: direction finding and location finding. For direction finding of taking sector, first through quesitionnaire Fill up informations on local winds were gathered. Then satellite images at two periods were compared through these images as well as field investigations, the erg morphological map was prepared. By studying wind regime and windrose drawing, the erosive winds were recognised. After recognition of taking sector (west and southwest sector), the location-finding phase was started. In this stage through geomorphological studying of taking sector and sampling into facies, the mineralogical and morphoscopical studies of sand dunes and taking sector sediments were done.At last with due attention to reasonings such as: the direction of Seif and Barkhan dunes (southwest-northeast), the settlement of Zibars in the west and southwest of erg, high intensity of energy for west and southwest winds, the existence of heavy minerals as Hematite and Amphibole in sediment samples, large median of samples (240 microns), the skewness of some samples towards coarse particles as well as low roundness factor (of taking sector samples), it was found that the sources of eolian sediments are close (<20 km) and inctude the followings:rangelands, abondoned farmlands and pistachio gardens on the east and southwest plains of Rafsanjan, the barelands or poorly covered grounds on the east pediments of Rafsanjan as well as beds of Shoor, Shahzadeh Abbas and Kabootarkhan rivers.

The development of a reliable wind forecast model plays a vital role in describing the variability and analyzing the time-series of the offshore and onshore wind profiles. In this paper, the analysis of the offshore and onshore wind profiles from the lidar and meteorological measurements based on two autoencoding architectures are presented.The historical datasets of the selected station variables from the:1lidar measurements and 2meteorological masts at 5–min and 10–min intervals are obtained. Two autoencoding model architectures (Conv2D and GRU encoding-decoding networks) in an unsupervised predictive operation are used for the time-series multivariable forecasting (1-288 horizons) and analysis of the:wind speed and wind direction, sectorwise windrose, CNR and prevailing air temperature. At the sampling period of 48 timesteps, the time-series wind speed and direction variations are analyzed in determining the measurement height with the steadiest wind flows for optimal loading of the large-scale wind turbine. Studied finding results of the offshore wind profiles at different heights revealed that the steadiest wind flow above 128.8 m height prevails but driven by the atmospheric effects. Also, the experimental findings revealed that the dominant wind flows of the onshore (10-20m height) are impacted by the local surface irregularitiesand atmospheric effects. Finally, the autoencoders performance is reported for the experimental offshore and onshore wind flowfor different station heights with and without the feature noise removal. Upon the validation and evaluation of the autoencoders with actual models, the proposed model architectures proved to be a fundamental forecast tool

Dust is a natural process in the desert areas. Strong winds on the dry soil surface make the particulate matter suspended in the air near the ground. In recent years, the influence of several natural factors has led to the further spread of dust in the western and southwestern parts of Iran. A storm take placed in the Khuzestan province and the northwest of the Persian Gulf, in February 17-19, 2017. The purpose of this study was to determine the source of dust as well as to study the conditions of the wind speed and direction and role of Low Level Jet in dust formation and transfer to Khuzestan and Persian Gulf. For synoptic analysis meteorological data provided from the ECMWF website. The horizontal distribution of dust investigated by MODIS satellite image and DREAM model. The HYSPLIT model also determined the dust trajectory. A coincidence survey showed that the northwest winds in eastern Syria and northwest of Iraq (the northern wind) were formed at the height of the fissure between east to west of Iran and a stack of compression from Turkey to north of Arabia. The synoptic analysis showed that northwest winds (Shamal) in eastern Syria and northwest of Iraq (northern wind) were formed between the pressure trough which is extended from east to west ward of Iran and pressure ridge from Turkey to north of Saudi Arabia. The northwest winds at the 925 reached 14 to 16 (28 to 32 Knt). The increase in the wind speed in the low altitudes of the atmosphere led to an increase in wind speed of 10 meters by 9 (18 Knt), which resulted in the release of dust particles into the atmosphere. During February 18 in southeastern Iraq and southwestern Iran, the LLJ developed. The result was an increase in turbulence and the vertical extension of the dust in the lower layers of the atmosphere. The synoptic north wind direction corresponded to the HYSPLIT model and Windrose. All of them represented the northwest wind direction and confirmed the transfer of dust from Iraq to the Persian Gulf. Satellite imagery and the DREAM model determined the deserts of Iraq and eastern Syria as the origin of the Persian Gulf dust. The MODIS imagery and the DREAM model showed the deserts of northwestern of Iraq and eastern Syria as the source of Persian Gulf dust storm.

Introduction The study of climate hazards such as heavy precipitation is very important due to its direct impact on flooding. Due to the climate change that the world has experienced, climate hazards have increased. What is certain is that humans cannot prevent the occurrence of climate hazards, but by being aware of these events in advance, under the influence of climate forecasts, they can reduce the destructive consequences of these hazards. Also, considering the very prominent role of humans in increasing the most important climate forcing, namely greenhouse gases, especially carbon dioxide, by managing fossil fuels and increasing new energy power plants, which are known as clean energies, climate changes that cause extreme events can be reduced. Another issue is the management of heavy precipitation to control large amounts of water for use in agriculture, which seems to be able to benefit from this weather event by taking measures. Another important point regarding heavy precipitation in the northwest region of Iran is to pay attention to the construction of residential areas in places far from rivers, which are vulnerable to flooding caused by heavy precipitation. The most important cause of extreme events such as heavy precipitation is currently climate change. The main factor causing climate change and desertification is greenhouse gases. The most important type of greenhouse gas is carbon dioxide. The main reason for the increase in this gas, which has a long life and is very poorly degradable, is humans. In other words, the main cause of the increase and intensification of extreme events is human misbehavior in dealing with nature. The northwest region of Iran is prone to heavy precipitation due to its mountainous topography and location on the main path of Mediterranean cyclones. This research was conducted with the aim of identifying the moisture sources of heavy precipitation in northwest Iran and also analyzing the instability indicators related to it.   Materials and Methods The study area in this study is northwest Iran, including West Azarbaijan, East Azarbaijan, Ardabil, North Kurdistan, and West Zanjan provinces. In this study, daily and hourly (3-hour) precipitation data and hourly (3-hour) wind data (speed and direction) were obtained from the Iranian Meteorological Organization (www.irimo.ir) for 23 synoptic stations located in northwest Iran during the period 1990-2019. The upper atmosphere data of the Tabriz station (the only upper atmosphere station in northwest Iran) were obtained from the University of Wyoming website (http://weather.uwyo.edu/upperair/sounding.html). The upper atmosphere data of this study were obtained from the NCEP/NCAR database (www.cdc.noaa.gov). Trial and error estimates showed that if the percentile is higher than 99 and the area covered by heavy precipitation is more than 30%, synoptic conditions will provide a good justification for heavy precipitation. In this paper, days when at least 7 stations in the study area simultaneously had at least 20 mm of precipitation were selected. In this study, using TTI, CAPE, KI, LI, SI and SWEAT indices, the state of atmospheric instability in northwest Iran was evaluated at a representative station in the region (Tabriz) on days of heavy precipitation (43 days). Based on factor analysis in the SPSS software environment, the main factors were identified from among the 6 indicators, then using cluster analysis, the main clusters were extracted and the Skew-T diagram of the representative days of each cluster was drawn and interpreted in the RAOB software environment. To select representative stations for the northwest region of Iran, 15% (3 synoptic stations) of the stations in the study area were selected based on altitude (meters), climate (number of heavy precipitation and average heavy precipitation during the study period), and large distance from each other (based on kilometers and geographical location). Using cluster analysis in the SPSS software environment, clusters were extracted based on the effective variables (relative humidity, wind vector, precipitable water) of the mid-level atmosphere in the northwest region of Iran. Then, the representative of each cluster was determined and for each representative day of heavy precipitation event (4 days out of 43 heavy precipitation events), in each of the 3 representative stations of the study area (3 stations out of 23 synoptic stations), the path and source of moisture of heavy precipitation were traced using the backward method (72 hours before the days of heavy precipitation in northwest Iran) and using global data analyzed at the  National Centers for Environmental Prediction and the National Center for Atmospheric Research (NCEP/NCAR) with a time step of 6 hours with a spatial resolution of 2.5 × 2.5 longitude and latitude for the levels of 850, 700 and 550 hectopascals, with the HYSPLIT web model. The wind gust diagram was drawn and interpreted using the WRPLOT software for the representative days at the representative stations of northwest Iran. The combined wind and precipitation diagram was drawn and interpreted hourly in the Excel software environment for the representative days at the representative stations of the study area.   Results and Discussion According to the criteria for heavy precipitation in this study, 43 extreme precipitation events were identified in the observation period (1990-2019). Using hierarchical cluster analysis using the Ward method with Euclidean distance, 2 main clusters were extracted from the 43 extreme precipitation events. The first cluster shows heavy precipitation events with dynamic ascent in the study area, and the second cluster includes heavy precipitation events with convective ascent in the research area. Of the two clusters, the first cluster has a higher frequency and indicates the dominance of heavy precipitation with dynamic origin over heavy precipitation with thermodynamic nature in the study area during the period under study. By drawing the Skew-T diagram in the RAOB software environment for representative days of each cluster, the instability conditions on representative days indicated the intensification and stability of atmospheric instability at levels above 850 hectopascals for the representative dynamic cluster. In the representative day's Skew-T diagram, the thermodynamic instability cluster was observed up to a maximum level of 850 hectopascals. Calculations showed that, considering the instability indices and the Skew-T thermodynamic diagram, the role of the convection factor in heavy precipitation  in northwest Iran was low and the dynamic factor was the main reason for heavy precipitation. The results of the study based on the windrose diagram indicate that the prevailing winds causing heavy precipitation  events blew from the southwest and had an average speed of 3.5 m/s. The output of the HYSPLIT diagram also confirms the southwest direction of the study area for the moisture input path of extreme precipitation. Also, the results of the combined hourly wind speed and precipitation diagram showed that the maximum wind speed and maximum precipitation on heavy precipitation  days were at 12:00 GMT, equivalent to 15:30 local time, which indicates the strengthening of the effective dynamic system in the region at this hour. In other words, the cyclone located at this hour, with the convergence created, has brought maximum humidity to the region and, with its sharp ascent, has provided the cause of heavy precipitation  in northwest Iran. Based on the calculations, the average atmospheric variability of precipitable water, relative humidity, and wind speed in extreme precipitation events in northwest Iran has been 16 kg/m2, 68 percent, and 20 m/s, respectively.   Conclusion Based on the research conducted in the northwest region of Iran, in the period 1990-2019 on heavy precipitation, the results showed that, considering the instability indices and the Skew-T thermodynamic diagram, the role of the convection factor in heavy precipitation was very low and the dynamic factor was the main reason for heavy precipitation. The results of the study based on the HYSPLIT model showed that the main path of moisture entry into the study area is the southwest and the main source of moisture supply for heavy precipitation is the Red Sea. The results of the study based on the windrose diagram indicate that the prevailing winds in heavy precipitation events blew from the southwest and their speed was 3.5 m/s on average. The combined hourly wind speed and precipitation diagram showed that the maximum wind speed on heavy precipitation days was at 12:00 GMT, equivalent to 15:30 local time, which indicates the strengthening of the effective dynamic system in the study area at this hour. Humans cannot eliminate weather hazards. Weather hazards are part of nature, and humans can only reduce the frequency and severity of these events. In the northwest of Iran, the best solution to deal with the risks caused by heavy precipitation  is to identify the causes of this event, such as the moisture sources that provide heavy precipitation , and to evaluate instability indicators that indicate the conditions for the formation of heavy precipitation. The next step is to inform the residents of the region, such as farmers, travelers, and others, about the occurrence of this event and warn them of the possibility of flooding. Insuring crops and residential houses, constructing residential houses in susceptible areas on high foundations with a height of 3 or 4 meters, increasing vegetation cover and planting seedlings with the aim of increasing soil permeability, dredging rivers to prevent water levels from rising due to sediment deposition, taking protective measures on river banks with the aim of reducing soil erosion in coastal areas, using mobile concrete dams during precipitation  in agricultural and residential areas with the aim of preventing possible flood damage during heavy precipitation , and avoiding unnecessary transportation due to reduced visibility, slipperiness, and flooding of urban and roadways are considered major solutions to reduce losses caused by heavy precipitation. The results of this study are in good agreement with the results of other researchers in terms of the dominance of dynamic instability in heavy rainfall, the occurrence of heavy rainfall in the spring due to convective causes, the occurrence of extreme rainfall due to the supply of moisture to the Red Sea by the Mediterranean cyclone, and the confirmation of the strengthening of cyclones causing heavy rainfall at 12:00 GMT.

Introduction Dusts are referred to as aerosol particles that are made up of different sources of land and humanization, and after which time, again, they fall on the surface due to their size and density (Salman Zadeh et al., 2012). This phenomenon can damage infrastructures, telecommunications and agricultural products and affect transport through reduced visibility and cause a lot of economic damage. (Song et al 2007., Cao et al 2016). The purpose of this study is measuring and spatial analysis of the city of Tehran in a one-year statistical period. Materials and methods In this research, we used the laboratory method to measure falling dust, collecting dust using Marble Dust Collector. For this purpose, the falling dust was collected using a Marble Dust Collector in 28 stations in Tehran during the statistical period. In order to analyze the spatial distribution of dust, dust was collected from 28 dust collecting stations, and Tehran PM10 data taken from the air quality control company, the number of construction urban under construction in Tehran were obtained from Tehran Municipality Organization, mean maximum wind speed parameters, average relative humidity, days of rainfall above 5 mm, the average temperature of Tehran taken from the country's meteorological organization in the one-year statistical period (1/10/96-30/9/97) to enter the Arc Map10. 5 environment and preparing the desired layers Were prepared. Statistical analysis of the data showed that Dust collected, pm10 and the number of running construction projects have regional (trend) behavior. Therefore, Universal trend is better suited. Due to the high preconditions for stagnation use of Universal trend In the area with fewer meteorological stations (Chitgar, Geophysics, Mehrabad and Shemiran) Universal trend is not applicable, Therefore, the IDW method was selected for climatic parameters. Also, the vegetation cover and factories file Shapes were taken and by analyzing Euclidean distance of each of these complications in GIS for Tehran, there impact on the dust in each area were considered. Then all the layers were weighed to determine the weights using the Reclassify tool. Then, using Expert Choice software, we compared all the layers two by two till estimate the value of each layer relative to the other layer. We multiplied the values obtained at each level. We transferred all layers to the Fuzzy Overlay tool. And draw up the final map of the spatial analysis of falling dust in Tehran city using the Gama 0. 9 function. Also, daily speed and wind direction data were received from the Meteorological Organization of the country during the one-year statistical period, (30/9/97-1/10/96). And with the help of the WRPLOT software for statistical analysis and the location of the wind, the windrose was drawn. Results and discussion The results of computations performed on the data obtained from the collecting of falling dust in Tehran showed that the weight of falling dust in the winter of 1396 is 18943. 5 tons, in the spring of 1397 it is equivalent to 27119. 5 tons, in the summer of 1397 it is equivalent to 17111. 2 tons and in the fall of 1397 it is equivalent to 23002. 3 tons. Also, the results showed that the highest falling dust was collected in spring, autumn, winter and summer, respectively. The spatial analysis map of Tehran's falling dust is a combination of 9 layers, based on the weight assigned to each layer. The results showed that the highest amount of dust in the winter of 1396 was found in west of Tehran. We had the lowest amount of falling dust in the north and northeast (regions 1 and 4). In the spring, summer and autumn of 1397, the halo of the most falling dust was displaced slightly eastward and settled in the southwest. The lowest amount of dusts in these seasons was located in the north and northeast. The halo with the lowest amount of dust falling has expanded further in the autumn than spring and summer. Conclusion The results of this study showed that the spatial distribution of falling dust varies in different seasons. Which shows that the source of falling dust in the city of Tehran is not uniform throughout the year. Field precise surveys have shown that the increase in falling dust in different parts of Tehran is directly related to urban construction. So that in the statistical year of the study, construction and subsequent falling dust has been less in eastern Tehran than its west and this increase is also associated with pm10. The largest amount of pm10 was reported from the west and southwest, which simultaneously collected the highest amount of falling dust. The highest density of factories and the lowest vegetation density are in these areas. The climatic factors also contributed to these conditions. So that, It was reported that the highest number of rainy days to exceed 5 mm was reported in north and north east of Tehran, where the lowest amount of dust was collected. And the highest average temperature in different seasons is reported from Southwest of Tehran, which has the highest amount of falling dust in spring, summer and autumn. But in winter climate conditions were slightly different from other seasons. So that, the highest relative humidity reported in other seasons from the West has been reported from north and northeast this season. The dust collected in winter is higher in the west than in the southwest. But the average maximum wind speed, which is in the west and south, is in the winter, spring and autumn to the west and southwest Which is from sand quarts of Quds, Shahriar, and Malard cities, especially the sandy-sand dune areas and abandoned agricultural land in Baharestan, Islam-Shahr and Robat-Karim, then dust from these areas enters Tehran west. In addition, the wind disperses the dusts generated by construction around the city. In the summer, in addition to the west and southwest, there is wind for north and south east. The northern wind comes from Shemiranat, bringing fresh air to the north and north-east of Tehran. The southeast wind passes from the Pakdasht sand and cement factories in Tehran and the abandoned agricultural land of Varamin and contains dust. The low wind speed in these areas gives more time to hangs off more particles. And of course, climatic conditions with the lowest relative humidity, the highest temperature, and a lack of rainfall above 5 mm also help to pollute the southern part of Tehran.