عنوان مقاله [English]
Mineral dust is the aerosol mostly affecting directly and indirectly radiation budget, temperature change, cloud formation, convection, and precipitation. In two recent decade, new sensors and models became available allowing new research activities on dust. Important studies considered atmospheric optical depth (AOD) as the key parameter for remote sensing and modeling of dust. The available model, satellite and ground-station datasets have been used to detect and characterize mineral dust phenomenon in affected regions and dust sources. Nonetheless, regional classification over the entire Iran using remote sensing parameters is still lacking.
Materials and methods
The present study aims to model and detect homogeneous areas of high dust concentration in Iran using dust AOD at 550 nm from the MODIS satellite Aqua and Terra sensors (2003-2012) with a spatial resolution 14 km2.
Among vector techniques, S-mode application as a principal component analysis (PCA) or empirical orthogonal functions (EOFs), is the most applicable and controversial method of classification for achieving the study target. The S-mode analysis is applied to the matrix made of the satellite observations at regularly spaced grid points of daily AOD values during the deacade 2003-2012. The S-mode analysis is applied to identify the geographycal distribution of high dust concentrations. PCA of the n x m matrix is applied and the scree test and North's rule were used to cut-off the statistically relevant components to be kept. Finally, in order to determine the best theoretical representation of the data, physical relationships embedded within the input matrix and localize the territory to simpler structures, specific modes of the residual components rotated by varimax. Varimax rotation means that each component has a few large loadings and many small loadings, and this assists in the process of interpretation if the results are due to the high values of explained variance. The rotated patterns, however, illustrate the simpler, more interpretable, and rational structures of mineral dust as principal modes. The identification of sub-regions and extreme dust loading was carried out using dust AOD values assuming the arbitrary thresholds of 87 percentile of and 95 percentiles, respectively. Therefore, the first threshold was used to determine sub-regions; consequently, the regions will have zero overlapping. The second threshold, used to extract the days with extreme AODs of each region. Herein, the Kolmogorov-Smirnov (K-S) test was used to infer whether the regional mean time series PCs of each different sub-region were statistically different.
Results and Discussion
The spatial map-patterns of dust, accounting 91% of AOD variability, have been divided into six subregions on Iran, which are the major centers affected by the dust. all of the sub-regions coincide with regional map-patterns depending on the distance and proximity to the dust source around the territory. Therefore, overlaping of identified dust areas related to dust extremes in each of Iran’s regions showed that the dust dominant patterns of Iran are under infuence of expansion and growth of dust extremes. The geographical location of sources areas and the special dynamic conditions over the mid-eastern atmosphere of Iran have been influenced by severe storms originating from the Karakum Desert. The northeast region is influenced by the dust plume originated from the Karakum Desert to Tabas Desert, which located in the southeast of the Kavir. These results showed that ground-based station studies, albeit long-term, have not been able to detect the northeast region as a distinctive region under infuence by southward dust plume.The same is true of the Central plateau, East and Southeast regions. In return, more focus was been on role of 120-day winds as a main cause of dust transport. Considering the mentioned reasons, previous studies have not divided borderline regions across Iran. Meanwhile, Weakness and intensity of dust-affected areas showed that the multiplicity and adjacent of dust flow to the southeast and east of the country are different and play a decisive role in the formation of east and southeast subregions. The shortcoming has also been observed for the west-northwest and southwest regions. In a case study (by horizontal visibility), were not only able to distinguish the dusty subregions because of limited observations in the interested area, but also could not analyze the identified subregions based on coressponding seasolality and extremes, which identified by 95 and 87 percentile in each of region, respectively. The detected extremes showed that identified sub-regions are function of the volume, growth and expansion of dust particles originated from the dust source regions across the Middle East and southwest Asia. Finally, the classification techniques showed that technical conversion of a dynamic phenomenon such as dust into simpler and more meaningful physical structures reveal geographically a simple and interpretable understanding of dust distribution in the territory of Iran. Morever, the use of remote sensed data utilized in the present study highligted the sub-regional distribution of dust over Iran that was neglected by previous studies providing a decription of a dynamic process that is complementary to the ground-based observation analisys. In some cases, a day event only based on ground-based observations may have had a high dust AOD with very horizontal visibility that has been ignored due to the level height of the dust layer. Therefore, the used technique integrates the knowlegde of dust based on grounded-measurement providing a large scale view of dust advection and diffusion.
The study results show that extraordinary dry conditions inside Iran combined with outside dusty sources have caused the country to be influenced by the high mineral dust aerosols. In addition to the domestic sources of dust, the study highlights that the mineral dust conditions in Iran are influenced by several arid and semi-arid sources beyonds its boundaries acting as dust sources. The subregions that form the spatial patterns of dust distribution in a six-distinct region of northeast, west-northwest, southeast, southwest, central and eastern of Iran are affected by the high dust aerosol optical depth (AOD) and are major centers of activity and high gradient areas (regions affected by dust) that follow trend distinctive seasonality. This has been able to illustrate identified sub-regions’s seasonalities and regional extremes by remote sensed data of atmospheric optical depth.The study results highlight that dust dominant spatial patterns of Iran are function of growth and expansion of dust extremes originated from source regions in the Middle East and southwest Asia. As a result, the present study showed that technical conversion of a dynamic phenomenon such as dust to simpler structures led to interpret geographically dust distribution.