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Spatiotemporal regionalization of atmospheric dust based on multivariate analysis of MACC model over Iran

TitleSpatiotemporal regionalization of atmospheric dust based on multivariate analysis of MACC model over Iran
Publication TypeArticolo su Rivista peer-reviewed
Year of Publication2021
AuthorsMohammadpour, K., Sciortino M., Saligheh M., Raziei T., and A. Boloorani Darvishi
JournalAtmospheric Research
Keywordsaerosol, Aerosol distribution, Aerosol optical depths, Aerosols, Arabian Peninsula, Atmospheric composition, Atmospheric dust, concentration (composition), Dust, Loading, Middle East, Multi variate analysis, Multivariant analysis, Multivariate analysis, optical depth, regionalization, Socioeconomic aspects, Spatial and temporal patterns, spatiotemporal analysis, Spatiotemporal evolution, Temporal pattern

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. © 2020 Elsevier B.V.


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Citation KeyMohammadpour2021