Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1016/j.atmosres.2020.105322 |
Spatiotemporal regionalization of atmospheric dust based on multivariate analysis of MACC model over Iran | |
Kaveh Mohammadpour, Maurizio Sciortino, Mohammad Saligheh, Tayeb Raziei, Ali Darvishi Boloorani | |
2020-10-17 | |
发表期刊 | Atmospheric Research
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出版年 | 2020 |
英文摘要 | Extraordinary dry conditions on the desert and arid areas in Iran, along with strong influences from surrounding dust sources in the Middle East and Arabia, have exposed the country to substantial amounts of dust aerosols with serious impacts on environment, health and socio-economic aspects. Considering this threat, daily aerosol optical depth (AOD) data over Iran obtained from the Monitoring Atmospheric Composition and Climate (MACC) reanalysis during 2003–2012 were used to analyze the spatial and temporal patterns of total AOD (TAOD) and dust AOD (DAOD). This study identifies the areas mostly affected by TAOD and DAOD in terms of daily average values and the areas associated with distinct temporal patterns, utilizing S-mode and T-mode principal component analysis (PCA). The analysis reveals six distinct sub-regions in southeast, west-northwest, northeast, east, central and southwest of Iran, which are among the major centers influenced by TAOD and DAOD extremes. The main findings of the T-mode results, consistent with TAOD and DAOD S-mode patterns, are (i) the maximum dust loading over the eastern, southeastern and southwestern subregions in March and May, (ii) dust loading with peaks in November over the eastern and northeastern sub-regions; (iii) maximum number of dusty days in July and August over southwest, (iv) maximum dust in July over southeastern and Central Iran, (v) a dust pattern with identical extent over the west and northwest sub-region in March and October and, (vi) a prevailing dust loading over the dry areas (Lut desert, Sistan plain and southwest edge of the territory) in October. The spatiotemporal evolution of dust is a function of the growth and expansion of dust extremes originated from various sources in Iran and the Middle East. The PCA methodology, through simplification of aerosol distribution to simpler structures, was also incorporated to provide a geographical interpretation of the highly sensitive territory of Iran. |
领域 | 地球科学 |
URL | 查看原文 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/299157 |
专题 | 地球科学 |
推荐引用方式 GB/T 7714 | Kaveh Mohammadpour, Maurizio Sciortino, Mohammad Saligheh, Tayeb Raziei, Ali Darvishi Boloorani. Spatiotemporal regionalization of atmospheric dust based on multivariate analysis of MACC model over Iran[J]. Atmospheric Research,2020. |
APA | Kaveh Mohammadpour, Maurizio Sciortino, Mohammad Saligheh, Tayeb Raziei, Ali Darvishi Boloorani.(2020).Spatiotemporal regionalization of atmospheric dust based on multivariate analysis of MACC model over Iran.Atmospheric Research. |
MLA | Kaveh Mohammadpour, Maurizio Sciortino, Mohammad Saligheh, Tayeb Raziei, Ali Darvishi Boloorani."Spatiotemporal regionalization of atmospheric dust based on multivariate analysis of MACC model over Iran".Atmospheric Research (2020). |
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