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Showing 3 results for West Iran

Dr Mohammad Ghasem Torkashvand,
Volume 5, Issue 2 (9-2018)
Abstract

  
Dust phenomenon is a natural occurrence that occurs widespread in arid and semi-arid regions of the world, especially in the sub-equatorial latitudes. This phenomenon is among the greatest environmental problems in the world. The release of this destructive climatic phenomenon in a scattered manner in the atmosphere varies in size, time and concentration. Since this phenomenon is influenced by the specific conditions of climate effects, its effects may continue to be as close as 16,000 kilometers from the source and cause abnormal environmental effects on the one hand, and numerous damage to agriculture, industry, transportation and telecommunication systems on the other hand. Dust storms, as an atmospheric destructive phenomenon, have created adverse environmental impacts for the west of Iran and caused many problems for the inhabitants of this region. Therefore, studying this phenomenon is necessary in order to achieve a comprehensive approach to deal with it. The present study was conducted with the aim of identifying the instantaneous atmospheric conditions, conduction and source of the dust storms with a synoptic modeling approach.
In this study, in order to investigate the dust storms structure in the southwest of Iran, the dust storm occurred on May 15, 2015 was selected. The reason for choosing the present day, based on reports from the Observatory and Monitoring Center of Ilam’s Environmental Protection Office, was the most polluted day of 2015, so the amount of aerosol recorded was 1200 µg/m3 in the air of Mehran City. To analyze the storm structure, a combination study was performed using NECP/NCAR reanalyzed digital data and output of dynamic and regional models. The first group consisted of three regional models of NAAPS, DREAM 8b and NMMB/BSC, and the second group included HYSPLIT dynamic model with backward method. NECP / NCAR data are also used in the synoptic analysis of the storm.
The average slope of air pressure in the sea level at the time of the dust storm in the west of Iran has increased and a high pressure difference of 20 hPa is observed between east and west of Iran, which is accompanied by a high pressure difference and severe winds in the southwestern borders of Iran. Also, the surface moisture flux of the soil has fallen sharply for the day of the storm occurrence in the study area. High advection in the Western part of Iran has been accompanied by a change in the density and mass of the air with heat, resulting in very rapid and intense air rotational movements around the Earth's surface; on the other hand, the coincidence of the positive and negative vorticity in a single significant amount in the formation of the lower level jet has caused the emergence of the dust storm to occur in the mentioned day. On the day of the dust storm, the orbital component of the wind speed was Western, and its velocity was more than 5 meters per second on the western borders of the country. The meridian component of the wind speed was also Southern. Therefore, the effect of present pattern on west of Iran during the day of storm dust has played a significant role. The optical depth index and surface dust concentration index in the NAAPS model have shown that dust concentrations ranged from 640 to 1260 µg/m3 to the west. Besides, the amount of sulfate in the region was estimated to be between 1 and 2 µg/m3. Comparison of the output of DREAM Bb and NMMB / BSC models showed an increase in concentration values per Dust surface unit on the day of storm occurrence. Based on the results of two models of DREAM Bb and NMMB / BSC in the case of western dust in Iran, it can be concluded that the effect of local factors and close proximity to the centers of the dust source have a significant role in the occurrence of present phenomena for western Iran. The simulation of the Dust storm direction with the HYSPLIT dynamic model and the backward method has shown two routes of dust entering the west of the country; a) Northwest - Southeast; b) West-East direction. The main origins of the first route, the northwest of Iraq and the east of Syria, and the second route were the center of Iraq.
Keywords: Spring dust storms, Regional modeling, HYSPLIT model, particles optical depth, West Iran
 
Kaveh Mohammadpour, Mohammad Saligheh, Ali Darvishi Bloorani, Tayeb Raziei,
Volume 7, Issue 1 (5-2020)
Abstract

Analysis and Comparing Satellite Products and Simulated
 Of AOD in West Iran (2000-2018)
 
Kaveh Mohammadpour, Ph.D. Student in Climatology, Kharazmi University of Tehran
Mohammad Saligheh, Associate Professor in Climatology, Kharazmi University of Tehran
Ali Darvishi Bloorani, Assistant Professor in RS & GIS, Tehran University
Tayeb Raziei, Assistant Professor in Climatology, SCWMRI, Iran
 
Introduction
Dust are the main type of aerosols that affects directly and indirectly radiation budget. In addition, those affect the temperature change, cloud formation, convection, and precipitation. In recent years, the increase of different sensors and models has made possible to research the dust. The most important studies about dust analysis has been considered of Aerosol Optical Depth (AOD) as the most key parameter, which are based on the use of remote sensing technique and global models for analyzing the behavior and dynamics of dust in recent two decades. To achieve this, it has used of MODIS and MACC to study and identify the behavior of dust in the last two decades over west Iran.
 
Materials and methods
Areas in this study are Ilam, Kermanshah, Kurdistan, Lorestan and Hamedan provinces. The area has studied of two data series such as: first is MACC data with a spatial precision of 14 km2 and a 3-hour time scale; and other one is MODIS sensor production on the Terra satellite with a 10-square-kilometers resolution. In order to analyze the dust in the area in the period 2000 to 2018, statistical methods and simulation has used of the AOD parameter in MACC and MODIS. Before any processing, the data regraded to 0.2 × 0.2 degrees in order to compare the data. Then, the average daily AOD formed in a 22 × 23 matrix with 560 pixels that presented with 3653 × 560 for MACC during 2003 to 2012 and 6489 × 560 for MODIS during 2000-2018. Average of daily AOD obtained of MACC and MODIS calculated using of statistical equations. Then, the spatial distribution of AOD during the dusty months for synoptic stations and total province surface extracted using of R packages during the daily time series of the periods. Finally, the spatial distribution of the obtained AOD interpolated using the kriging function.
 
Results and Discussion
The average annual AOD obtained from Deep Blue algorithm from MODIS was less than MACC in all of the interested stations, except for Hamedan and Khorramabad stations, and provinces surfaces.
Correlation of AOD between MODIS and MACC shown that the correlations is high between model and sensor data (R2 = 59). In addition, the spatial correlation map shows 0.38 to 0.76 in which indicates a significant relationship between the MACC and MODIS pixels and the relationship is more in the western provinces of the area than the northeast of the region (Hamedan). The monthly comparison of the mean of AOD of the sensor and the model in the whole the area shows a highest correlation between the AOD in February and October.
The interpolation of the spatial distribution in the decade of the study (2003-2012) in MACC showed that the spatial variations of AOD is decreasing from the south of Ilam to the north of Kurdistan and reached the lowest level in the north of Kurdistan province. In general, the findings of annual and seasonal spatial distribution (dry period) of dust showed that MACC overestimated AOD compared to MODIS in the area. Nonetheless, the dust pattern in both of the sensor and the model increased from south to north. Although, the dust pattern is more regular in the sensor than the model. The spatial distribution of dust in Ilam, Kermanshah, and Kurdistan provinces in MODIS and MACC shows that dust in the southern point of the Ilam province has the highest concentration and the lowest is observed in the northeast of Kurdistan province. This spatial distribution of dust showed that dust in western provinces of the area follow latitudinal trend , in which is influenced by the high topography of Kermanshah and Kurdistan provinces and the proximity of Ilam province to dust sources in the distribution of dust intensity.
 
Conclusion
The results showed that there was a significant correlation between the sensor and the model and the coefficient was more than 0.4 in all months on the area. The findings of the annual amount of dust in MODIS showed that the amount of dust in the years 2000 to 2009 has increased in whole areas and from 2009 onwards, this annual trend has been reduced by 2018. MACC findings also showed that the AOD has been growing up in the period, although AOD amount have had a steep slope by 2010, but since 2010, dust has a steady slope. Therefore, West Iran has experienced two active (before 2010) and inactive (after 2010) periods in dust during an 18-years period on the area. The findings of MODIS and MACC in the study area indicate that the monthly distribution of dust from April to August has the highest concentration. In general, the annual and seasonal spatial distribution (months with the highest AOD) of dust indicates that the intensity of AOD in MACC was higher than MODIS in the area. Although the sensor and model has a roughly similar pattern and increases from south to north, but the trend in MODIS is more regular than MACC.
 
Keywords: Aerosol Optical Depth (AOD), MACC, MODIS, West Iran
 
 
 
 
Nabi Mohamadi, Behrouz Sari Saraf, Hashen Rostamzadeh,
Volume 10, Issue 3 (9-2023)
Abstract

 Nowadays, due to global warming, drought and the occurrence of cold periods and heat stress, the study of climatic variables is very important. Therefore, in this research, the long-term forecast of temperature changes in northwest Iran in the base period (1985-2014) and three periods of the near future (2021-2050), the medium future (2051-2080) and the distant future (2100- 2081) was paid. For this purpose, 2 extreme temperature indices including Warm spells duration index (WSDI) and cold spells duration index (CSDI) and Maan-Kendall trend test were used to check the changes. To predict the changes of the profiles in the future period after evaluating 7 general circulation models (GCMs) from the sixth report model series (CMIP6) from two optimal models under three socio-economic forcing scenarios including SSP1-2.6, SSP3-7.0 and SSP5-8.5 was used. The spatial distribution of the trend of changes in the Warm spells duration index (WSDI) in the base period showed that its maximum core is located in the south and southwest of the region, and its amount decreases by moving towards the north and northeast. Spatial changes of the Cold spells duration index (CSDI) are characterized by its maximum cores in the western regions and around Lake Urmia and minimum cores in the central and northern regions of the study area. According to the results, the average Warm spells duration index (WSDI) and of the Cold spells duration index (CSDI) are equal to 5.53 and 3.80 days per year, respectively, and the maximum and minimum Warm spells duration index (WSDI) are 1.8 and 2.7 days, respectively Piranshahr and Parsabad stations and the maximum and minimum and the Cold spells duration index (CSDI) are also 5.7 and 1.32 days corresponding to Zarineh and Marivan stations. Examining the trend of changes also showed that in most stations, the WSDI index has an increasing trend, and this trend has become significant in some stations, but the CSDI index has a decreasing trend and is not significant in any of the stations. The evaluation of different models with different error measurement indices also showed that MRI-ESM2-0 and MPI-ESM1-2-L models have the best performance in simulating temperature extreme in the studied area. The distribution of changes in the future period also showed that the WSDI will increase in most stations and based on all three scenarios, especially the SSP5-8.5 scenario, but the CSDI trend will decrease in most stations and based on the SSP3-7.0 and SSP5-8.5 scenarios will be significant.

 

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