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Showing 4 results for Modis Sensor

Forogh Momenpour, Nima Faridmojtahedi, Shabnami Hadi Nejad Saboor, Hossien Abed, Samaneh Negah,
Volume 1, Issue 4 (1-2015)

Mountain systems have an important role on meteorological variations. Different components of the mountain affect the atmospheric parameters and have essential role in atmosphereic circulation. Garmesh wind is one of the most well-known phenomena that are related to mountain systems. In this research, mechanism of garmesh wind are identified using database of garmesh wind  in the last 29 years  and using remote sensing technology from 2005 to 2010.

To survey the Synoptic and dynamic conditions of atmospheric patterns in the Garmesh wind’s events in the region, SCDATA  of several synoptic stations in Gilan province, including Rasht, Bandar Anzali, Astara and Jirandeh  are used which had continuous long-term data in 1982-2010period After Identification of days with Garmesh wind, daily images of Modis sensor of  terra and aqua  satellites in visible band and 7-2-1  band are monitored for checking the cloudiness on the  both  sides (southern and northern slops) of Alborz mountains and  data of Jirande station in southern slop of Alborz mountains are used for detecting atmospheric phenomena like precipitation and snowfall. Also for studying the synoptic and dynamic pattern of this phenomena, reanalysis data from NCEP/NCAR were  used.

    In this research, Based on the presence or absence of the atmospheric phenomenon (like rainfall and snowfall), three categories were identified.  In the first category, Garmesh winds were happened in clear sky conditions and without any atmospheric phenomena on both side of mountain’s slope. In the second category, only cloudiness was seen at the time of the Garmesh wind.  In the third category, precipitations (in this research, snowfall) were seen in southern slope of Alborz Mountains.

Statistical analysis of Garmesh wind in central plains of Gilan

Totally, Occurrence of Garmesh wind was 479 days in Rasht, during 1982-2010. The frequency of occurrence of this phenomena was in January, February, November and December and rarely, in September and June.  Clouds that observed in the time of Garmesh wind were: Altocumulus (type 4), Cirrus, CirroCumulus.

Patterns of Garmesh wind mechanisms on western half of Alborz Mountain:

  • B1. Garmesh wind without any phenomena

    This category includes11 cases of total 47 studied cases. 29 January 2008 is an example of clear sky condition in the time of Garmesh wind. In this pattern, in the surface zonal extension of   Mediterranean dynamical low pressure’s contours from west of Caspian to Gilan plain and at the same time formation of cold high pressure cell on Zagros mountains caused strong pressure gradient   on southern coastal zone of Caspian Sea, As it led to the the increase of wind velocity in Rasht airport synoptic station from 11 kilometer per hour in 00 UTC to 36 kilometer per hour in 12 UTC. Dominance of warm core on southern Caspian versus dominance of cold surface air on Iran Plateau indicates adiabatic warming in northern slope of Alborz Mountains.

  • B2. Garmesh wind with cloudiness

   This category includes 34 cases of total 47 studied cases.  Free of air mass’s patterns in the surface and conditions of atmospheric flows in low-troposphere that are similar to previous category, transition of height trough in mid-troposphere and high-troposphere  can be name variant component verses previous category.

  • B3. Garmesh wind and precipitation (snowfall)

   This category includes 2 cases of total 47 studied cases. At the same time, surface high pressure was on Iran Plateau and low pressure system was on Caspian Sea and also Gilan providence that caused the formation of Northerly stream and west-east stream to southern coastal zone of Caspian Sea and backward of Alborz Mountains like other patterns, snowfall occurred on southern slope of Alborz Mountains. Strong southern and south-western stream and strong positive vorticity   on southern slope of Alborz Mountains by deep height trough in low-troposphere has an important role on intensification of vertical motions on lee ward of Alborz Mountains.

    Garmesh wind is an atmospheric phenomenon that occurs as a result of interaction between atmospheric systems in synoptic scale and topography on back ward of mountain. In the other words, existence of Alborz Mountain’s as a great wall has an important role in the interaction between synoptic systems and formation of Garmesh wind.

    Formation of Garmesh wind phenomena in Gilan province, is affected by extension of Siberian high pressure’s counters and sub-tropical high pressure on central of Iran Plateau and also existence of advection of pressure’s counter  like sub-polar  low pressure and or the Mediterranean Sea on north of Alborz mountains are required. Without any notification to origin of air masses, three categories has been observed based on existence or absence of Phenomena (in this research, sowfall)

    In 700 and 500 hPa, Geopotential height patterns and relative vorticity field indicate that in the first category, wide parts of Iran is affected by high height and negative vortisity like low troposphere,  during peak hours the wind. But in the second and third category (specially in third category ) existence of upper trough and  easterly extension of trough caused to reduction of height and formation of strong positive vorticity in upper level and all over of air column  in  both south and north slopes of Alborz mountains.

Miss Elham Karegar, Javad Bodagh Jamali , Abbas Ranjbar Saadat Abadi , Mazaher Moeenoddini, Hamid Goshtasb ,
Volume 3, Issue 4 (1-2017)

Dust particles are important atmospheric aerosol compounds. The particles are resulting performance of strong winds at the soil surface desert areas. Sources of dust are 2 types: 1- Natural Resources 2- Human Resources. Iran is located in the desert belt which this problem cause increased the frequency of dust storms, especially in South East (Sistan) and South West. China Meteorological Administration Center classifies storms based on particles type, visibility and speed storms to 4 kind: Floating Dust, Blowing Dust, Sand/Dust Storm and Sever Sand/Dust Storm. In general, the effects of dust storms in 7 of Environment (particles into remote areas, the effect of dust particles on the material, climate, oceans and deserts), public health and health (increase of respiratory diseases , cardiovascular problems, digestive, eye, skin, reduced hearing, infections, reduced life expectancy and premature death, etc.), economic (unemployment, road accidents, damage to communication lines, air, land, sea, increase water turbidity in water utilities, creating uncertainty for all economic activities, etc.), Agriculture and Livestock (negative effect on the growth of plants and animals, reduced productivity and diversification, intensification of plant and animal pests and diseases, rising costs maintenance of livestock, etc.), socio-cultural (poverty and the loss of local jobs, destruction of subcultures, rural migration to the cities, closure of educational premises, industrial units, services, etc.) and military-security (disabling weapons, food and beverage contamination, the threat of sensitive electronics and power transmission systems, and reduce the useful life sitting on warehouse equipment, logistics cargo weight gain, etc.) can be evaluated. One way to identify, evaluate and forecast dust storm modeling. Dust cycle consists of 3 parts, dust emissions, dust and subsidence transfer dust that can be simulated by models.

In this study using the WRF_Chem model with FNL[1] input data and GOCART schema, sever dust storm in Sistan region was simulated to date 14 & 15 July 2011. Satellite images of the event was received by the MODIS sensor. Dust concentration data was received from the Department of Environment. The dust storm code, minimum visibility data and maximum wind speed data was received from the, Meteorological Organization.

The results of the simulation for dust concentration which peak amount of dust was for 21Z14July2011 and 03Z15 July 2011. Model output showed maximum wind speed 20 m/s with North to South direction in the study area. The model predicts maximum dust concentration for the latitude 31 degree North and longitude 54 degree East to 66 degree East (Within the study area). MODIS sensor images showed clearly the sever dust storm. Simulated time series in Figure 3-1 Changes in dust concentration during the event show in the Sistan region. As can be seen from the peak of the concentration of dust in 21 hours on 14 July (350 micrograms per cubic meter) and 03 hours on 15 July (425 micrograms per cubic meter) 2011 was created. Model simulation and satellite images indicated which the Sistan region, especially dry bed of Hamoun wetland in East of Iran was main source of sand and dust storm. Also, based on the model output blowing wind direction from North to South on Iran which converging these currents in East Iran caused by strong winds in the lower levels (According to the meteorological data), arise dust, increasing the dust concentration (According to Department of Environment data), increasing the dust and being transferred to the Southern regions, especially  Oman sea. To identify the source of the sand and dust storm, the path of the particle and anticipated this event cant actions and warned to stop and reduce effects its. . Simulation of dust particles in the resolution of 10 and 30 kilometers, the plains of Sistan in Iran's East region as the main source screen. The findings suggest that compliance with the maximum concentration limits on known sources of particles (especially Sistan plain dry bed of plain wetlands) is. Check drawings wear rate showed that the source of dust in the Sistan region, particularly the high potential of our wetlands dry bed of soil erosion in wind activity 120 days during the hot and dry conditions, and silt and clay up to thousands of kilometers away from their source transfers. Vector lines on maps wear rate, indicative of converging flow north-south and severe dust storms in history is this. It is better than models forecast dust events and rapid alert

[1] Final Reanalysis

Hamed Haidari, Dariush Yarahmadi , Mostafa Karampour,
Volume 7, Issue 3 (11-2020)

Dust phenomenon is one of the climatic fronts that is often formed in the dry and desert regions of the world, and is known as a natural hazard. Occurrence of walnuts causes dust, damage to the environment and the occurrence and exacerbation of respiratory, cardiac, air traffic and threats of tourism, agriculture and so on. Also, in the health section of the compounds in calcium dust, more than 2.5 g of it causes the appearance of kidney stones, and blood vessels. Iron causes swelling of the conjunctiva and retinal inflammation, as well as the syndrome. Magnesium causes depression, depression and dizziness of the individual. Short-term breathing of aluminum leads to coughing and irritation of the lungs and prolonged breathing causes damage to the lungs. In recent years, the identification of dust source areas has attracted the attention of researchers in numerous studies, and have introduced various areas around the world as the main source of generous production. The country of Iran, and in particular the Western and Southwestern logic of Iran, is constantly experiencing the phenomenon of dust and its problems. In the west of Iran, desert areas are located in the deserts of southern Iraq, Saudi Arabia and far away from Syria and North Africa. The geographic location of the southwestern part of Iran and its proximity to these deserts have led to a frequent occurrence of the phenomenon of dwarfs, which are different throughout the year.
In this research, two categories of data were used: the first group is data on climatic elements or unstable elements.
The annual climatic layers of the region were used for a 30-year statistical period of 2016- 2016. Measurement data on the temperature of surface temperature was obtained from a MODIS sensor in a 17-year statistical period (2000-2016). The second group of data layers and information on the ground factors or factors were stable. The layers of these variables included:
  1. The digital elevation layer of the area with a precision spacing of 30 meters from this layer was used as the elevation layer of the area.
    2. The slope of the region, in percent, which is the layer derivative of the digital elevation model and derived from the same specifications of the DEM layer.
    3. The surface layer of the surface layer that was taken from the MODIS surface coating product
    4. Layer of vegetation on the surface of the earth, which was also taken from the 1 kilogram MODIS vegetation cover
    5. Soil layer that was prepared by the country's water and soil organization
 The method of conducting analytical and statistical research in which the main objective is the determination of areas conducive to the formation or expansion of dust cores. In this regard, the establishment of land-based and climate databases is the first stage of work, after forming the required databases, the formation of information layers These data are in the GIS environment. In order to form these layers, the interpolated models in GIS were used and the optimal model was selected in such a way that less error values ​​were obtained. After forming the existing layers, we classified and weighed each layer based on the AHP weighting algorithm. Finally, due to the assigned weights, the overlaying of the weights of the layers in the GIS environment was obtained and finally a potential capability map of the formation of local dust collectors in Lorestan province was obtained.
 The rainfall factor is the most important and most important factor in determining the areas susceptible to becoming dusty. The weight of this factor in determining and identifying areas susceptible to dusty cores was equal to 239%. Vegetation factor, which was prepared using the NDVI indicator of the MODIS product, was the second factor in the development of dust-prone areas with a weight of 199.99. Relative humidity factor is the third factor or component that influences the determination of suitable areas to become the local focus of dust. The weight of this factor is equal to 0.15. The wind speed factor is in the fourth place in terms of determining the areas susceptible to dust. The relative weight of this factor is estimated at 116.0. As shown in Table 14, slope and elevation factors are the least important factors that can play a role in the production and development of dusty centers. The weight of these factors in identifying areas susceptible to formation of dusts is 0.024 and 032.2, 0 is detected. The calculated incompatibility index for this weighing is as high as 4.8, as shown in Table 15, which indicates that the contradiction between the offered weights of indices relative to each other is less than the allowed threshold (12).
 Neutbay expressed the highest concentration of areas susceptible to dust mites in the eastern region, especially the northeast of the province, which includes the cities of Azna and Aligudarz. There are also parts of this category in the southern regions of the study area, including the cities of Poldokhtar and Rumshagan. In the central regions of the province as well as in the northwest of the province including the Khorramabad, Delfan, Dynasty and Dorood districts this class is not observed. In the southern parts of the city of Kohdasht, small parts of the floor of the potential centers of dust are also observed. This flooring has the most risk of becoming a dusty focus. The power source of many of the province's dusty incidents can also be said to be areas where some of them are currently potential sources of dust. Since they have played a major role in the identification and detection of these areas, rainfall and vegetation cover, these areas are exactly in line with parts of the province, which, firstly, have a mean rainfall of less than 250 mm, and the density of vegetation is less than 2 / 0 (NDVI index), which represents a very poor vegetation and, in fact, a lack of viable vegetation. In terms of land use, these areas, or inferior land, or very rangelands, are very weak.

Mohammad Sadegh Ghadam Khair, Reza Borna, Jafar Morshedi, Jebraeel Ghorbanian,
Volume 10, Issue 3 (9-2023)

Extensive and massive agriculture, along with other agricultural activities such as animal husbandry, industrial activities in the southern half of the province, has created and intensified extensive changes in the environmental resources and natural structure of the province. This extensive change can show its effects and consequences in the destruction of forest lands, the transformation of rich pastures into poor pastures and barren lands, severe soil erosion, and finally the creation and development of internal centers of dust. and intensify the severity of dust incidents in the province. Dust events have profound and significant effects on agriculture and soil fertility, health and hygiene, disruption and destruction of industries and power plants, and negative effects on the environment, including the deterioration of forests. Airborne particles, which are mainly driven to the region by dust storms, are one of the important components of the atmospheric system. They can not only change the albedo of the energy balance by acting as cloud particle nuclei, or ice nuclei.
Materials and Methods
The study location of this research is Khuzestan province, which is one of the most challenging provinces in the country in terms of environmental hazards. This province, with an area of about 6.5 million hectares, occupies about 4% of the country's area. Dust is one of the major and most important challenges of this province. Its destructive effects can be traced in various dimensions, such as the quality of water resources, the quality and performance of agricultural products, industries and energy transmission networks, and the air quality of cities. Three categories of data have been used in this research. The data of the first category is related to the data of widespread dust days in Khuzestan province. These data were obtained from the dust codes of the current air condition (ww parameter of synoptic stations of the province) during the statistical period of 2000, 2020. The second category of data was actually the remote sensing data of MODIS sensor, which included the Aerosol Optical Depth (AOD) product of MODIS sensor (MOD04 product) and Aerosol Exponential Index (AEA). These two indicators are dimensionless but with different directions. In the AOD index, higher numbers represent more aerosols in the atmosphere and in the AEA index, in addition to the presence of dust in the place, it also provides the size of the aerosol particles. Finally, the third category of data is the reanalysis data related to incoming net shortwave radiation (SNSR), which was taken from the reanalysis data of the European ECMWF database version ERA5 with a spatial resolution of 0.5 arc degrees.­

In this research, it was tried to investigate the influence of the dust event in the context of fluctuations and daily changes in the amount of net shortwave radiation received on the earth's surface. The results of the investigation of three cases of widespread dust in the province showed that in these three cases of widespread dust, aerosol particles are generally in the central, southern and western parts of the province (plain and lowland areas of the province) from the type of medium to large particles (index angstrom between 0.5 and 1) and in the eastern and northeastern parts, it was of the type of coarse particles (angstrom index less than 0.5). In the context of the impact of dust events on the amount of shortwave radiation received by the earth's surface, it was seen that in the dust event of July 22, 2010, the Angstrom exponential index indicates the presence of coarse particles in the atmosphere near the earth's surface and the AOD index also indicates the presence of dense dust in the entire area of the province. The received net shortwave radiation (at 12 noon or 09 UTC) was about 194 watts per square meter (about 28 percent) lower than the average for the same month. This drop rate was less in the other two dust waves, whose AOD and Angstrom index values indicated finer and less concentrated dust. In the dust wave of June 19, 2012, the amount of net shortwave radiation received was only 5% (25 W/m2 at 12 noon or 09 UTC) less than the long-term average, and this drop in the dust event of May 12, 2018 was equal to 28 W/m square (about 4% drop compared to the average of the same month).

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