JOURNAL OF METEOROLOGY AND ATMOSPHERIC SCIENCES (JMAS)
Year:2018 | Volume:1 | Issue:1 |Papers Count:7

In this study, Rossby wave activity flux was used to investigate the budget, direction, and intensity of the incoming Rossby waves into the Middle East and Iran, and their relation to the positive precipitation anomaly in April and October of 2018. A dry period (April and May 2008) was selected to compare the wave flux in the wet period. Precipitation data from the weather station of I. R. of Iran Meteorological Organization (IRIMO) has been used to calculate the precipitation anomaly. NCAR / NCEP data were used to compute wave activity flux. Results showed that two factors manage the energy budget in the Mediterranean region: convergence and divergence of the wave activity, and the sources and sinks of energy. During the wet period, wave activity is stronger, and there is an area of intense wave divergence on the east of the Atlantic Ocean. The waves from the Atlantic Ocean, by passing the Mediterranean Sea covers Iran. In the dry period, eddy activity in the west of the Atlantic Ocean is weaker than the other parts. Therefore, the convergence of wave stream function on the Atlantic Ocean and also the weakness of the Rossby waves in this area, followed by the divergence of wave stream function on the east of the Mediterranean Sea and of course Iran, as well as the lack of appropriate eddy activity in this region, have caused drought in this period.

The streets play an important role in preserving pollution and fuel consumption. Therefore, geometrical and meteorological conditions are of interest to researchers. The geometrical parameters include building shape, orientation and aspect ratio (W/H), which is the ratio of the building height (H) to building width (W). The meteorological parameters include ambient wind speed, direction and thermal stability. Furthermore, the design and construction of streets and buildings should be considered, since the presence of buildings in the streets can affect meteorological parameters. For example, there must be enough wind speed to eliminate the pollutant in the street. In recent decades, numerical models have been one of the most commonly used tools for urban planning in ventilation optimization units. In this study, the air flow and dispersion of pollutants in a narrow street in the city of Yazd are investigated numerically, using the combination of a computational fluid dynamics model (Fluent model) with a mesoscale model (WRF). The WRF is a numerical weather forecast, and a simulation of an atmospheric systems model that is designed for research and operational applications. In the case of Yazd, Imam Street was chosen as an area for the CFD model, since the north-eastern end of this street leads to a vacant area which makes defining the boundary conditions straightforward. The CFD model is simulated for this city. The simulation with FLUENT software requires a computing domain and meshes that are generated using the Gambit software. The initial and boundary conditions should be determined in order to provide a numerical solution of partial differential equations. The inlet mass and wall boundary conditions are used for pollutant removing from linear source and at the boundaries where the fluid is enclosed by a solid. According to the results, the boundary conditions were obtained from the simulation of the WRF model. At first, the airflow was simulated by the WRF model near the surface without considering urban canopy. Then the pollution dispersion in the street canyon and around the build-up was simulated with high resolution by the FLUENT software in three dimensions. In this study, a meteorological parameter such as wind speed has been investigated. The WRF model was executed on the 12th of January 2015 at 8 am, and the FLUENT model was coupled to calculate the flow field on the 13th of January 2015 at 9 am; there was a high-pressure system on this day in the area. The FLUENT model was tested using wind tunnel data. The results of Miao et al. (2013) and meteorological data have been used to validate the WRF model. Comparison of the coupled model results shows that the CFD model is required to determine the pollutant dispersion pattern from the linear source, and this pattern cannot be solely obtained from the wind blowing environment of the WRF model due to these patterns being influenced by various blowing environment speeds and directions, the effect of buildings on each other, vortices, and other factors. The two-phase mixture model is used for two-phase flow in the FLUENT software in this paper. The k-ε RNG turbulence model is used for turbulence. The effect of geometric parameters such as the longitude of the street, and of meteorological parameters such as wind speed, has been investigated. The pollutant dispersion pattern from the linear source is influenced by the speeds and various directions of the blowing environment in the build-up area, and cannot be solely obtained by using WRF model. Therefore, the use of the CFD model is required in this simulation. Results: In summary, the results of this study suggest that the pairing of the WRF-CFD model can be considered as an important tool to study and predict the urban flow and dispersions in dense, built-up areas.

Atmospheric circulation strongly modulates precipitation patterns throughout the south of Iran. Characteristics of synoptic types were chosen to investigate their relation to the spatiotemporal distribution of precipitation within the south of Iran. In this study, we examined the inter-annual variability of precipitation in the southern region of Iran, and established links among the large-scale circulation patterns. In this region, the majority of precipitation occurs during the rainy season from October to May. The study applied the empirical orthogonal function (EOF) analysis of the monthly precipitation anomaly data obtained from 302 meteorological stations for the 1981– 2010 periods. In most months the first mode explains more than 50% of the total variance of the precipitation. Spatiotemporal fluctuation in precipitation over the studied area can be attributed to moisture transport by dynamic factors. This study shows that the position and strength of high pressure over the Arabian Peninsula play an important role during the wet and dry years. The results show that during wet years’ moisture flux in low and middle levels from the west of the Indian ocean, the Gulf of Aden, and the Red sea is transferred by the high pressure circulation to the central, North Arabian Peninsula and Southern Iran. This high pressure circulation coupled with the Eastern Mediterranean trough over the west of the Arabian Peninsula at the level of 700hPa. Some parts of moisture flux transferred from the Gulf of Aden and the Red sea in the middle and higher levels. In dry years, the anticyclonic circulation is strengthened in the west of the Arabian Peninsula, and blocks moisture advection into the region from the Indian Ocean.

The purpose of this study was to evaluate the role of rainfall during wet periods and meteorological droughts in recent years to decrease the impact of river flow droughts in the Karkheh basin. To this end, the hydrology-land surface coupled model ALSIS-HBV was used. The application of this model to an undisturbed period (when the system is only affected by natural factors) and to a disturbed period (the system is affected by both human and natural factors) will allow the defined goal to be achieved. The threshold level method was used to monitor meteorology and hydrology drought. Findings show that the time delay between meteorological drought and river flow drought in different sub-basins is between 15 to 90 days. When meteorological drought is more severe and prolonged, the time required to improve river flow drought will be increased. In the undisturbed period, the river flow response is rapid and river flow droughts are improved with a delay of 1 to 3 months. The process of improving the river flow is slowed down during the disturbed period, and this trend has been slower in the last decade. Comparisons of P/Qobs ratios (precipitation to river flow observations) and P/Qsim (precipitation to simulated river flow) show, due to minor variations of P/Qsim, that the coupled model simulates the river flow response to precipitation anomalies. However, in actual conditions of the basin, due to human involvement in nature, this ratio has been increased in disturbed periods. The results of drought recovery for river flow for the dry period of 2008-2013 with increasing rainfall scenarios show that in the sub-basins of Gamasyab, Qare Sou, and the entire Karkheh basin, in order to recover drought of the river flow in the high flow, rainfall should be higher than the long average and requires extreme rainfall. In the years under study, increasing the mean temperature and evapotranspiration from surface water could be a detrimental factor in high flood recovery.

In this study, GP, ANN, BCSD and SVM were used to evaluate the performance of simulation models. The modeling based on the large scale data of atmospheric general circulation and the mean daily temperature of the Ahwaz synoptic station was conducted during the period of 1971-2004, and the evaluation of each model was based on the correlation coefficient and modeling error between simulated and observational data. The results of modeling indicated that the correlation coefficient between observation and simulation data in the SVM model is more than in other models, and its value is 0. 9960. The correlation coefficient for the GP, ANN and BCSD models is equal to 0. 9393, 0. 9384, and 0. 4936 respectively. Moreover, the results of the evaluation of the simulation error were calculated using the RMSE and NSE criteria for SVM to be 0. 677 and 0. 955 degrees Celsius respectively. Similarly, these values are 1. 644 and 0. 969 for GP, 1. 657 and 0. 968 for ANN, and 6. 174 and 0. 661 for BCSD. Therefore, SVM has better performance in modeling the mean daily temperature than other methods, and modeling the mean daily temperature by the BCSD method is less accurate than other methods. The GP method has a weak advantage over ANN, and it is recommended to use the minimum and maximum temperatures for the more precise performance of these two models.

Prediction of climate change using the recorded data from reference periods requires precise methods that are able to accurately detect fluctuations and predict changes for future periods. In this study, six multivariate regression models, ANN, SVR, ANFIS, SVM and GP, were investigated and compared for down scaling the daily mean temperature of the Urmia synoptic station, using 26 prediction parameters taken from the fifth IPCC report. The average daily temperature values measured from 12/03/1961 to 20/12/2005 were used for the analysis. 16 of the 26 parameters having a high correlation with the average daily temperature values were selected for all methods using the Pearson correlation test. To investigate the modeling errors, the coefficient of determination, Root Mean Square Error, and effectiveness criteria were used. The results of the evaluation of the accuracy and modeling error showed that among the smart models, GP, ANN, ANFIS and SVM, the Genetic Programming model has the least amount of errors, and in the regression model (multivariate regression and support vector regression) support vector regression has the lowest error rate and the highest accuracy of simulated daily temperature values of the Urmia station. In general, the results of the simulation of the mean daily temperature indicate that regression has better accuracy than smart methods. Since in this study, we only used the data from the Urmia synoptic station, so the results are only valid for this station, and it is not safe to generalize the results for all stations.

In this study, the minimum values of precipitation in heavy and extreme rainfalls are determined to be 42. 8 and 84. 2 mm, respectively, by applying the percentile index to the daily rainfall data of 8 meteorological stations during the years 2001 to 2015. Subsequently, 30% of the 612 rainy days were selected, where heavy and extreme rainfalls occurred in at least 3 out of 8 stations. Moreover, out of these, 13 days were selected considering more time and space distribution and 4 days were selected for synoptic analysis. Furthermore, the reanalysis data of some parameters such as sea level pressure, wind and geopotential height were extracted from the NOAA database at different pressure levels. The synoptic maps were then designed using the GrADS software and finally these were analyzed in terms of synoptic – dynamic. The analysis of the maps shows that the occurrence of heavy and extreme rain in Bushehr province results from the establishment of a blocking system of Rex or Omega blocking type at 500hPa level, and the development of Sudan’ s low-pressure system in the southwest and western strip of Iran. The limitation of low pressure in the southwest of Iran by two high pressure centers, one from the north to the south of Iran, and the other from Europe to north Africa, creates a strong convergence area, and results in the dynamic climb of air and extreme rainfall in the north of the Persian Gulf. The results also indicate that the main sources of moisture are the Arabian Sea, the Oman Sea, the Red Sea, as well as the Persian Gulf, and in some cases the Mediterranean Sea.