The Effect of Teleconnection Factors and Rossby Wave Propagation on Atmospheric Patterns in Ilam Heavy Rainfall and its Predictability using WRF Model

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Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:
In the 1987–2018 statistical period, unprecedented rainfall amounts of about 320mm in 72 hours were recorded at Ilam in October 2015. This heavy rainfall was studied from the perspective of teleconnection, the flux of the Rossby wave activity and synoptic-dynamical analysis. To investigate meteorological quantities, the ERA5 data with horizontal resolution of 0.25 degrees were used. To determine the predictability of the above precipitation, the WRF model was run for three nested domains with respectively 36, 12 and 4 km horizontal resolutions and then simulated rainfall values were compared with the observations. The results show that based on the flux of the Rossby wave activity, the system is received Rossby-wave activity mainly from the middle latitudes. Moreover, the combination of the strong Sudanese and Mediterranean low-pressure systems, the impact of the Chappala tropical storm as a source of injecting moisture into the region, the blocking created in the middle troposphere, the ridge formed in the southern latitudes of Iran, and the impact of the Zagros Mountains are the main factors affecting this heavy rainfall event. The results of teleconnection study showed that the moderate to strong descending branch of the El Nino prevented the eastward movement of the phase 2 and strong MJO convection. The MJO phase 2 activity has extended and strengthened the ridge in the southern latitudes of Iran, leading to several days of system persistence and continuous rainfall in the study area. Further, the positive NAO phase has led to strong pressure gradients and cyclonic reinforcement in the eastern Mediterranean. The simulation results of WRF model also showed correlation coefficients of 88% with 95% significance level. The 8% error rate between simulation and observation precipitation showed the remarkable model's ability to predict this rainfall.
Language:
Persian
Published:
Journal Of Geography and Regional Development Reseach Journal, Volume:18 Issue: 2, 2021
Pages:
113 to 137
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