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Kaveh Mohammadpour, Mohammad Saligheh, Ali Darvishi Bloorani, Tayeb Raziei,
Volume 7, Issue 1 (5-2020)
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
Kaveh Mohammadpour,
Volume 8, Issue 4 (3-2022)
Volume 8, Issue 4 (3-2022)
Abstract
Application of multivariate techniques in-line with spatial regionalization of AOD over Iran
Introduction
Models, satellites and terrestrial datasets have been used to detect and characterize aerosol. Nontheless, micoscale classification using remote sensing parameters considers as a deficiency. Thus, regionalizion and modeling aerosol without regard to political boundaries or a specific stations over Iran demonstrates the spatial distribution of simple AOD structures.
Materials and methods
Present study attempted to simulate and detect homogeneous areaes of aerosol in Iran using AOD (areosol optical depth) datast at 550 nm across Iran. Among the eigen techniques, principal component analysis (PCA) is the most applicable and controversial classification applied as multivariate analysis approach. In the line of the target, PCA, S-Mode separate the AOD subgroups with similar correlations. In the mode, m time series apply to each n station or grid points as a variable in the analysis, which is the territory of the region or geographical area. Mathematically, if the input data column in the Z matrix is applied as mathematical variables and the Z matrix has n points in the time series and m is the time step, then in the Zs decomposition has 3654×9985. In addition, the scree test and North's rule were used to cut-off the principal components and to select the number of appropriate special vectors to be kept.
Results and Discussion
For the study purpose, 85 percentaile of loadings were used to determine AOD areas over Iran. Using the method, the spatial patterns of Iran's aerosolshave been divided into six subregions, which are the major centers affected by the AOD. These major AOD hotspots affect by AOD extermes that are originated from aerosol surrounding sources. So that, the geographical location of sources areas have caused the northeastern atmosphere of Iran to be influenced by severe storms originating from the Karakum Desert. The same is correct concerning the East and Southeast regions. While, the intensification and transfer of aerosol from the Sistan plain to the south is increased AOD load over southeast Iran. Moreover, this study revealed a set points associated with distinguishing spatial differences between the west-northwest and southwest regions as well as central region that have not addressed in previous studies because of focus on ground-based observations. Also, the method illustrated that formation of the identified regions are a function of the volume, growth, and spread of aerosol particles resulting from the source regions in the Middle East. Finally, the classification techniques converting dynamic phenomenon such as aerosol into simpler structures presented a interpretable understanding of the geographical distribution of the phenomenon.
Conclusion
The present study identified the spatial patterns of AOD hotspots into six distinct regions including northeast, west-northwest, southeast, southwest, central and eastern Iran affected by the aerosol as well as major centers or high gradient areas. In addition, the present study not only supported by previous studies, but also it make sense a regionalization that was neglected by former studies, whileseperated the boundaries of the AOD areas without considering provincial boundaries. Overall, the classification techniques, PCA, simplified a dynamic phenomenon such as aerosol into a simpler and illustrated geographical and interpretable understanding of the spatial distribution of the phenomenon.
Keywords: Aerosol Optical Depth (AOD), Multivariate Techniques, Regionalization, Iran
Kaveh Mohammadpour, Ali Mohammad Khorshiddoust, Gona Ahmadi,
Volume 10, Issue 2 (9-2023)
Volume 10, Issue 2 (9-2023)
Abstract
Introduction
Dust storm is a complex process affected by the earth-atmophere system. The interaction between the earth and atmosphere is in the realm of the climatologists and meteorologists, who assess atmospheric and climatic changes, and monitor dust spread. Dust is the main type of aerosols which affects directly and indirectly radiation budget. In addition, altogether they affect the temperature change, cloud formation, convection, and precipitation. The most important studies about dust analysis have considered the use of remote sensing technique and global models for analyzing the behavior and dynamics of dust in recent two decades. To achieve such a goal, this paper has used MODIS and NDDI data to study and identify the behavior of atmospheric dust in half west of Iran.
Materials and methods
The western region of Iran is the study area. The data used in this study are divided into two categories: ground-based observations in 27 synoptic stations extracted from the Iran’s Meteorological Organization during the period (1998-2010) and satellite MODIS images during the first to fourth days of July 2008 as atmospheric dust extremes. Data was analyzed by using ArcGIS and ENVI software and NDDI index.
Results and Discussion
According to results, interpolated map for the number of dusty days during the study period over the western half of Iran showed that the scope of study area does not involve an equal system aspect quantity of occurrences. The number of dusty days occurrences increase from north toward south and the sites located in northern proportions of the area have experienced lower dust events. In contrast, maximum hotspots are occurring over southwestern sites such as: Ahvaz, Ilam, Boushehr and Shiraz. Therefore, principal offspring of dust input has been out of country boundaries and arrived at distant areas. Also, based on results obtained using satellite remote sensing images and applied NDDI index, maximum of intense dust cover is observed over Fars, Ilam, Boushehr and Ahvaz provinces on the first, second, third and fourth of July. However, the lowest rate of index situated in extent far such as: East and West Azerbaijan provinces. Thus, parts located on the north of the study area experienced less dusty days and the maximum dust cores were located in the southwestern (mostly Khuzestan). The long-term results were consistent with the daily average of NDDI index in the whole study area and indicated the hotspot areas (Ilam, Ahvaz, Omidyeh, Bushehr and Shiraz) during the first to fourth days of July 2008. However, the level of dust cover in the region has reduced when a wet and cloudy synoptic system passes over the central and northwestern parts of the study area.
Conclusions
The climatic interpolated map interpretation indicated that increase of dust concentration based on ground-based stations, which are consistent with dust concentration, is overshadowed by the latitude and proximity of sources of dust source in the Middle East. Also, the long-term climatic results of ground-based observations were consistent with the NDDI index calculated on dust extremes in the whole study area and in the southern areas (Ilam, Ahvaz, Omidyeh, Bushehr and Shiraz) during study days of July, 2008. Therefore, dust occurrence increases from north to south and the maximum hotspots over southwestern confirm the proximity of the south western region of Iran to deserts and sedimentary plains and their direct relationship with dust sources in the Middle East. These regions highlight the volume and expansion of dust outbreaks, which were well detected due to the satellite imagery and spectral characteristics of MODIS for monitoring changes in the dust phenomenon.
Overall, the use of satellite remotely sensed data/images not only cover the ground-based observation datasets gap to identify, highlight, and analyse the dust phenomenon, but also takes a much more geographical approach in analysing environmental hazards such as dust. It is also suitable for studies of atmospheric compounds such as atmospheric aerosols.
Dust storm is a complex process affected by the earth-atmophere system. The interaction between the earth and atmosphere is in the realm of the climatologists and meteorologists, who assess atmospheric and climatic changes, and monitor dust spread. Dust is the main type of aerosols which affects directly and indirectly radiation budget. In addition, altogether they affect the temperature change, cloud formation, convection, and precipitation. The most important studies about dust analysis have considered the use of remote sensing technique and global models for analyzing the behavior and dynamics of dust in recent two decades. To achieve such a goal, this paper has used MODIS and NDDI data to study and identify the behavior of atmospheric dust in half west of Iran.
Materials and methods
The western region of Iran is the study area. The data used in this study are divided into two categories: ground-based observations in 27 synoptic stations extracted from the Iran’s Meteorological Organization during the period (1998-2010) and satellite MODIS images during the first to fourth days of July 2008 as atmospheric dust extremes. Data was analyzed by using ArcGIS and ENVI software and NDDI index.
Results and Discussion
According to results, interpolated map for the number of dusty days during the study period over the western half of Iran showed that the scope of study area does not involve an equal system aspect quantity of occurrences. The number of dusty days occurrences increase from north toward south and the sites located in northern proportions of the area have experienced lower dust events. In contrast, maximum hotspots are occurring over southwestern sites such as: Ahvaz, Ilam, Boushehr and Shiraz. Therefore, principal offspring of dust input has been out of country boundaries and arrived at distant areas. Also, based on results obtained using satellite remote sensing images and applied NDDI index, maximum of intense dust cover is observed over Fars, Ilam, Boushehr and Ahvaz provinces on the first, second, third and fourth of July. However, the lowest rate of index situated in extent far such as: East and West Azerbaijan provinces. Thus, parts located on the north of the study area experienced less dusty days and the maximum dust cores were located in the southwestern (mostly Khuzestan). The long-term results were consistent with the daily average of NDDI index in the whole study area and indicated the hotspot areas (Ilam, Ahvaz, Omidyeh, Bushehr and Shiraz) during the first to fourth days of July 2008. However, the level of dust cover in the region has reduced when a wet and cloudy synoptic system passes over the central and northwestern parts of the study area.
Conclusions
The climatic interpolated map interpretation indicated that increase of dust concentration based on ground-based stations, which are consistent with dust concentration, is overshadowed by the latitude and proximity of sources of dust source in the Middle East. Also, the long-term climatic results of ground-based observations were consistent with the NDDI index calculated on dust extremes in the whole study area and in the southern areas (Ilam, Ahvaz, Omidyeh, Bushehr and Shiraz) during study days of July, 2008. Therefore, dust occurrence increases from north to south and the maximum hotspots over southwestern confirm the proximity of the south western region of Iran to deserts and sedimentary plains and their direct relationship with dust sources in the Middle East. These regions highlight the volume and expansion of dust outbreaks, which were well detected due to the satellite imagery and spectral characteristics of MODIS for monitoring changes in the dust phenomenon.
Overall, the use of satellite remotely sensed data/images not only cover the ground-based observation datasets gap to identify, highlight, and analyse the dust phenomenon, but also takes a much more geographical approach in analysing environmental hazards such as dust. It is also suitable for studies of atmospheric compounds such as atmospheric aerosols.
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