In this research, the sensitivity of the meteorological elements (such as mean temperature, relative humidity and wind speed) to different physical parameterizations in the numerical forecast model (WRF) was evaluated to simulate the climate of the city and adjust the Urban Heat Island of the study area.To study urban environmental issues, the Urban Canopy Model (UCM) was coupled to the WRF model. Several experiments were performed to achieve optimal configuration for simulation in the period from 18-21 August 2016 in the stable atmospheric conditions in summer. Selection of the most appropriate configuration with the least error is proposed as an appropriate setting for urban climate simulations and the study of Urban Heat Island (UHI). Increasing surface reflections to reduce UHI in the range was applied. Two indices of Root Mean Square Error (RMSE), and Mean Bias Error (MBE) were used to evaluate the predictive performance of the model and its corresponding observational values. The results showed that in the province of Tehran, in general, all configurations estimate the air temperature and wind speed less than real and relative humidity more than the actual value. In Alborz province, all configurations estimate the air temperature and wind speed more than real and relative humidity less than real value. By increasing the reflection of urban levels, the mean temperature of Tehran and Alborz provinces decreases 0.6 and 0.2 ° C, respectively. Wind speed, especially in urban areas, increases somewhat. We also see an increase in relative humidity (especially in urban areas) in the studied areas.

The present study investigated the impacts of NAO and ENSO on the precipitation in the southern shores of Caspian Sea. The accumulated monthly and annual rainfalls from 5 synoptic stations during the years (1956-2017) were taken through Islamic Republic of Iran Meteorology Organization (IRIMO) and the Multivariate Enso Indices (MEI) and NAO activity years are obtained from National Oceanic Atmospheric Administration. Pearson correlation was used to investigate the relationship between indices and precipitation amounts of selected stations. The results showed that there was a significant relationship between precipitation and NAO index in some months in all stations but this correlation was not following a particular pattern in all the stations. The maximum correlations were observed at Babolsar and   Anzali station and the least correlation was found at  Gorgan stations. The correlation between precipitation and different phases of NAO showed that there was a positive correlation between precipitation and negative phase of the index in Ramsar station and a negative correlation between precipitation and positive phase in the Gorgan station.The results of the Pearson correlation show a significant correlation between the MEI and rainfall amounts in the autumn in some stations in the early winter. In Review drought and wet periods with both Indicator it was observed that the behavior of the stations in the El Niño period, which was with different phases of the NAO was not entirely harmonious but the coefficient of 89% of rainfall in normal and more than normal during the period of El Niño showed that Elnino is better fitted to normal and more than normal rainfall in these stations also coefficient of 60%  of weak to severe droughts in the Lanina period in the selected stations Indicates that the LaNina phase was more related with severe droughts in the under studied period.

By employing urban growth and development modeling, it is feasible to delineate a developmental trajectory that aligns with the specific circumstances of a city, considering environmental factors, natural elements, and population dynamics. The aim of this research is to propose an urban development model for Shushtar, which can serve as a valuable tool for analyzing the intricate processes of urban transformations. To accomplish this objective, two datasets were utilized: urban land use maps (including educational spaces, healthcare facilities, residential areas, etc.) and Landsat satellite imagery for key land uses such as rivers, barren lands, and forests, spanning three time periods: 1991, 2004, and 2014. These datasets were processed using GIS and MATLAB software. Existing urban land use maps were digitized and subsequently updated using Landsat satellite imagery. Subsequently, influential parameters in urban development were introduced as inputs to the Adaptive Neuro-Fuzzy Inference System (ANFIS) algorithm. After training the model for the years 1991 and 2004, the predicted results of urban development using the algorithm were compared with the actual situation in 2014, demonstrating a high accuracy of 93.7%. The land use change map, resulting from the change detection process, can be generated based on multi-temporal remote sensing images and their integration with urban land use maps, enabling an analysis of the associated consequences. The use of intelligent algorithms in this research has facilitated modeling with a high level of accuracy. The obtained results are deemed acceptable, and this development has also been predicted for the upcoming years.

Considering that urban land-use change in metropolises such as Tehran has been increasing in recent decades; Therefore, the formation of the thermal island phenomenon in the city can be studied as one of the environmental problems. Increasing construction, density, and building heights will change the complexes' geometry and shape, followed by changes in climatic conditions and micro-urban climates. Therefore, in this study, we tried to investigate urban geometry's effect on forming a thermal island in Tehran. The study region in this research includes regions one, two, and three of Tehran.
The methods used in this research included (1) Oak's numerical equation and algorithm design to simulate the intensity of the heat island. In the first stage, digital GIS data including building blocks (parcels) in polygon format and street widths, which were prepared and prepared by Tehran Municipality based on the 2016 detailed audit plan, were used. (2) Modeling was performed in Envi-met software to study the effect of city geometry on wind. The results of the studies showed that the two factors of building height and street width (ratio (H/W)) play an important role as two key factors in studying urban geometry; therefore, in studying the intensity of the heat island, the factor of building height and high-rise construction can play an important role in the formation of the heat island. However, the higher the height of the building compared to the width of the streets, the more it acts as a barrier against the heat island. The intensity of the heat island adjusted with the Oak equation showed that the factor of building roughness coefficient can be an important factor in adjusting the intensity of the heat island. Spatial analysis of images and outputs of the Envi.met model showed that the two main factors of construction density And the height of the building has a greater impact on wind speed transmission than the slope and topography of the area. Therefore, in the study of urban design for future studies, appropriate planning and proper management of resources are needed for the climatic comfort of residents, which can be designed to be beautiful and safe cities by considering the principles of architectural safety.