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
In this research, the effect of two indicators OMI and RMM of Maden Julian fluctuation on the frequency of dust storms in Abadan, Ahvaz, Bostan, Bandar Mahshahr, Dezful, Ramhormoz and Masjed Soleyman located in Khuzestan province during six months (April to September) of the statistical period (1987 - 2021) was reviewed. Pearson's correlation coefficients between dust data and indicators were investigated and its results were calculated in the form of income zoning maps and the frequency percentage of each indicator for positive and negative phases. The results of the research findings indicate that there is a direct and significant relationship between the positive and negative phases of both indicators with dust, except for Dezful station in the positive phase of OMI and the negative phase of RMM and the highest correlation coefficient for Bandar Mahshahr and Dezful station is between -0.7-20.77 is in the positive phase of the RMM index. The relationship between the Madden Julian Oscillation and dust showed that between 51 and 59 percent of dust storms occurred in the negative phase of the OMI index and 40 to 49 percent in its positive phase. In the RMM index, 56 to 63 percent of dust storms occur in its negative phase and 37 to 50 percent in its positive phase. In fact, the negative phase of the RMM index has a higher percentage of dust storms than 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 leads to the occurrence of dust storms for most of the stations in Khuzestan province. Tracking the paths of dust entering Khuzestan province with the HYSPLIT model shows the movement of particles from Iraq, Arabia and the eastern parts of Syria towards the studied area.
