Tooba Alizadeh, Majid Rezaei Banafsheh, Hashem Rostamzadeh, Gholamreza Goodarzi, Hedar Maleki, Hamzeh Alizadeh,
Volume 24, Issue 74 (9-2024)
Abstract
The aim of this study was to identify the epicenter and co-occurrence factors of dust storm wave from 1 to 3 November 2017 in Kermanshah. To investigate the synoptic conditions of the causes of this phenomenon, from the European Central Center (ESMWF) mid-term weather forecast data set with a resolution of 0.125 degrees of arc including, geopotential height, omega, sea level pressure, orbital and meridional components, humidity. The Lagrangian method of HYSPLIT model was used to orient the source of dust particles. in this study, dust storm WRF-chem was simulated using a paired numerical weather forecasting model. Finally, through the processing of MODIS satellite images, its scope was determined. Examination of HYSPLIT tracking maps shows that two general paths for dust transfer to the area can be identified. 1- The northwest-southeast route, which passes through dust cores formed in the deserts of Iraq and Syria, transports dust to the western half of Iran. 2- Southwest to west of Iran and Kermanshah, which is the main source of dust on November 2 and 3, The source of the particles is Kuwait, northern Saudi Arabia and part of Iraq. The spatial distribution of the dust interpreted by the MODIS sensor images is consistent with the spatial distribution of the dust concentration simulated by the WRF-chem model.
Mrs Fatemeh Vatanparast Galeh Juq, Dr Bromand Salahi, Batoul Zeinali,
Volume 25, Issue 77 (6-2025)
Abstract
This study investigates the impact of the OLR MJO Index (OMI) and the Real-time Multivariate MJO (RMM) of the Madden-Julian Oscillation on the frequency of dust storms in the stations of Abadan, Ahvaz, Bostan, Bandar Mahshahr, Dezful, Ramhormoz, and Masjed Soleiman, located in Khuzestan province, during the period from April to September 1987-2021. Pearson correlation coefficients were computed to assess the relationship between dust data and the indices, and the findings were depicted through zoning maps. Subsequently, the frequency percentage of each index for both positive and negative phases was quantified. The results indicate a direct and significant correlation between the positive and negative phases of the indices and dust occurrences (with the exception of Dezful station), particularly during the positive phase of the OMI and the negative phase of the RMM. The highest correlation coefficients, ranging from 0.77 to 0.72, were observed for Bandar Mahshahr and Dezful stationsduring the positive phase of the RMM index. Analysis of the relationship between the Madden-Julian Oscillation and dust storms revealed that between 51% and 59% of dust storms in Khuzestan province occurred in the negative phase of the OMI index, while 40% to 49% occurred in the positive phase. In the case of the RMM index, 56% to 63% of dust storms were associated with its negative phase, in contrast to 37% to 50% linked to its positive phase. Notably, the negative phase of the RMM index exhibited a higher percentage of dust storms compared to the negative phase of the OMI index. According to the results of the Monte Carlo test, the displacement of the positive and negative phases of the RMM index significantly contributes to the occurrence of dust storms at most stations in Khuzestan province. Furthermore, tracking the pathways of dust entering Khuzestan province using the HYSPLIT model indicates the movement of particles originating from Iraq, Arabia, and the eastern regions of Syria toward Khuzestan province..
