فهرست مطالب علیرضا صادقی نیا

The COVID-19 epidemic is considered a geographical phenomenon, and its impact on decision-making and daily life is significant. Geographic information systems (GIS) and spatial techniques play crucial roles in analyzing the spread of COVID-19 globally. Studies using spatial analysis have highlighted the importance of social and health variables in infection and mortality rates, despite existing uncertainties about the effects of meteorological variables. Given Iran's climatic diversity, it is valuable to identify the key spatial factors influencing COVID-19. Therefore, this study aims to model and determine the factors affecting the COVID-19 epidemic based on available data.

This study investigated the factors influencing the distribution of COVID-19 infection rates using global and local spatial regression methods. Seventy-three cities were selected, with data on COVID-19 infections available from March 10 to June 20, 2019. The factors considered were altitude, population density, average age, the ratio of the population over 55 years to the total population, and meteorological parameters, including humidity, temperature, pressure, and wind speed. Their relationships with the disease were analyzed using spatial statistics methods. Stepwise regression identified population density, air pressure, average age, and wind speed as significant predictors, and the occurrence of the disease was modeled using the Ordinary Least Squares (OLS) technique. Due to the unstable relationship between the independent and dependent variables, the Geographically Weighted Regression (GWR) technique was used. Principal Component Analysis (PCA) and SPSS software were employed to address spatial variability and multicollinearity.

The results showed that the OLS model was statistically significant, with variance values explained by the model being non-random. However, the explanatory variables had an inconsistent relationship with the dependent variable in both geographic and data spaces. The residual distribution deviated somewhat from normal, indicating model instability. Thus, the GWR technique was applied for modeling. PCA addressed multicollinearity (due to a cluster pattern in meteorological variables), reducing meteorological factors to one component, explaining nearly 70% of the variance. The model improved by consolidating the average age and the ratio of the population over 55 into one factor. Subsequently, population density, meteorological factors, and age demographics were utilized as predictive variables in the GWR model. A 10% increase in the adjusted R-squared of the GWR model (63%) demonstrated its relative improvement over the OLS model. Moran's spatial autocorrelation test indicated that, while the cluster pattern of residuals was less pronounced in the GWR model than in the OLS model, it remained significant at the 99% confidence level. Hot spot analysis at the 95% confidence level identified the western parts of Kurdistan province and the northern and western parts of Khuzestan province as hot spots (areas of significant underestimation), and the eastern parts of Hamadan province and the northern parts of Bushehr province as cold spots (areas of significant overestimation). Thus, at least one variable affecting disease occurrence was not considered. Other potential factors, such as cultural, health, and genetic variables, were not included due to unavailability or measurement difficulties.

This study highlights the importance of demographic and environmental factors in COVID-19 infection rates and provides a foundation for further research in the study area.

Agricultura sector due to extensive interaction with the environment, the agriculture receives the greatest impact from climate change and threatens rural communities depending on agriculture activity with serious risks. The purpose of this paper is to evaluate the effect of climate change on agriculture and to choose adaptation strategies in Najafabad. The research method in this study is descriptive and analytical and the data was prepared by field work and a questionnaire. The statistical population is Najafabad Farmers. The sample size is 300 farmers who were selected through Cochran's formula in the simple random. The main tool of the research was a questionnaire, the validity and reliability of were confirmed by experts with Cronbach's alpha 0/760. The analysis of the collected data was done with statistical methods and SPSS software. Results showed that farmers are aware of the increase in drought and the decrease in precipitation and the weather getting warmer. For 51% of farmers, crop diversity is one of the adaptation strategies. Almost 53% of farmers believe that the use of chemical fertilizers and pesticides increases the capacity to adapt to climate change. 66% of farmers have chosen advanced irrigation systems to deal with climate change. The results of logistic regression showed that the variables of gender, awareness of climate change, information received from extension service offices and adaptation to climate change play an important and decisive role in the production of agricultural products. Three regression models as agricultural product, unemployment and food shortage were compiled all of which were significant.

 Investigating the spatial and temporal distribution of lightning occurrence and the trend of lightning occurrence in Iran.

 Monthly spatial and temporal distribution of lightning occurrence investigated based on HRMC data in the range of 25° E - 65° E and 15° N - 42° N. The trend of lightning occurrence was studied based on LRMTS data in about twenty years (1995-2014) using a standardized regression slope.

 Iran is divided into eight regions based on the characteristics of lightning activity. The minimum of lightning and convective activities occur in the country's center and east. The maximum occurs in the northwest from June to August, in the west, southwest, and south from November to May, and in the south in September. The activity of the Red Sea convergence zone influences the maximum occurrence from December to May in the southwest and west of Iran. The most significant increase in the occurrence of lightning occurred in the southeast of Iran in the summer, the Caspian Sea in the winter, the area between the Black Sea and the Mediterranean in the fall, and finally, in the south of the Persian Gulf in the spring. The most significant decrease has been observed in the center of the Red Sea, the Black Sea, and the Mediterranean, respectively, in the summer season.

 Considering the effect of convective activities on Iran's rainfall regime, we can expect an effective change in the characteristics of Iran's rainfall regime due to global warming.

The present research used a numerical simulation technique known as the Discrete Fracture Model (DFM) to examine the propagation of shale gas in fractured porous media. It employed a novel mathematical model for seepage flow, incorporating the application of the 'cubic law' for flow in fractures and Darcy's law for the seepage flow in the matrix. The impact of fracture aperture on flow behavior was simulated by solving a set of nonlinear, partial, differential equations using the finite element method (FEM). Through this work, a sensitivity analysis of the significant parameters, including hydraulic fracture numbers and permeability, hydraulic fracture aperture, and wellbore length, on the productivity of a shale gas reservoir was conducted. Hydraulic fracture permeability with increasing oil production (more than twice) had the greatest effect on the wellbore productivity. Furthermore, the simulation results showed that augmenting the number of hydraulic fractures from 4 to 15 resulted in a production increase of over twofold. Also, it was observed that the production rate increased due to the existence of a positive correlation between the fracture aperture size and the drainage area. The outcome of this research showed the significance of hydraulic fracture characteristics and its ensuing effects on the productivity and feasibility. In order to validate the accuracy of the numerical model, the pressure distribution in a single fractured reservoir was compared with the pressure contour of a phase field discrete fracture model (PFDFM). The results indicated that the proposed method (FPM) was precise, convergent, and extremely promising.

The purpose of this study is to evaluate the readability level of 11th grade geography textbook based on students’ gender and school type. The Gunning FOG, Flesch and Cloze test indexes were used to examine the difficulty level of the book. The findings of the study revealed that the book is appropriate for an undergraduate course, but it is difficult for 11th grade students. The readability scores of lessons showed that the content of the book is not organized from simple to difficult. The mean score of the 11th grade students was 34% in the cloze test. As a result, the content causes stress and frustration for learners due to its difficulty. The results showed that female students had a higher mean score of reading ability than male students, but this difference was not statistically significant. Also, students’ reading score in special public schools was significantly higher than that in conventional public schools. In addition, there was a significant positive correlation between students' reading ability score and geography lesson score.

Blizzards are severe forms of snowstorms that occur in the middle and upper latitudes of the northern hemisphere in winter season. The devastating disaster of a snowstorm with dangerous blizzard conditions on February 3 to 9, 1972, with more than 4,000 dead in Iran, is one of the most destructive snowstorms in the world. In this study, aspects of the synoptic scale at the time of occurrence of this phenomenon have been investigated using the reanalysis data of NCEP/NCAR and ECMWF databases. The variables used include geopotential height, sea level pressure, air temperature, specific humidity, relative humidity and zonal and meridional velocity of wind. In addition, the parameters of omega, relative vorticity, and zonal jet index have been calculated to explain the performance of the atmospheric system. The results indicate the dominance of atmospheric block (Rex) system in two separate phases from 3 to 6 February and from 7 to 9 February. The role of the artic polar vortex in injecting cold air into low latitudes and a noticeable decrease in temperature before a snowstorm and blizzard in saturating the atmosphere and providing the moisture needed for snowfall is quite evident. The zonal index of Jetstream showed the significant jump of the core of subtropical jet stream at the time of the occurrence of this extreme phenomenon.The zonal index of Jetstream showed the significant jump of the core of subtropical jet stream at the time of the occurrence of this extreme phenomenon.The zonal index of Jetstream showed the significant jump of the core of subtropical jet stream at the time of the occurrence of this extreme phenomenon.

In this study, in order to identify the most important evidence of climate change in the southern coast of the Caspian Sea, temperature and precipitation changes were studied using 20 indices during 1968-2017. The results showed that the intensity of precipitation significantly increased, but the number of days with precipitation significantly decreased. Despite the increase in rainfall intensity, the total annual rainfall has decreased, because of the number of rainy days and length of wet periods significantly decreased. Seasonally, spring rainfall decreased and summer rainfall increased. All the extreme temperature indices showed significant trends. On average, the increasing trends of the minimum annual temperatures and maximum annual temperature were 0.51 ° C and 0.31 ° C in per decade, respectively. The frequency of hot days and hot nights significantly increase with an increase rate of 1.5% and 2.7% per decade, respectively. Also, the frequency of cold days and cold nights significantly fell with a decrease rate of 1.1% and 1.3% per decades, respectively. In general, the heating trend of the nights was stronger than during the days. The warm spell duration index showed a clear increase, with a rate of 2.6 d per decade. Comparison of the results of this study with the findings of global studies showed that the increasing trend of temperature in the southern Caspian coast is in line with the trends observed in global studies, but the decreasing trend of precipitation in the Caspian region is opposite to the increasing trend of global precipitation.

Urban spaces have a great impact on the public health of citizens. Almost research on the relationship between the urban physical environment and citizens 'health has relied solely on assessing citizens' perceptions of the urban environment. In this article, the relationship between the general health quality (GHQ) of citizens' and the measured physical environment aspects of the city has been investigated.

The present research is applied in terms of purpose and is field method in terms of nature and  method. For this purpose, after literature reviewing, in the first stage, the sample size was determined using Cochran's random method and in the second stage, using hierarchical cluster sampling method and georeference questionnaire technique, survey data of GHQ from 384 citizens of Kerman were Collected in 2019. Also, with the formation of the statistical block of the general population-housing census in 2016 in the GIS, the characteristics of the physical environment of Kerman, including; The variables of residential density(RD), ground commercial density(GCD), street conecection density(SCD) and green space density(GSD) and land use mixing ratio(LUMR) and walk-ability index were calculated. Finally, the partial correlation values of Kerman urban form variables with the values of general health quality index were estimated and analyzed.

Partial correlation between GHQ values had a significant positive relationship with age and gender and a significant negative relationship with education. Also, the values of GHQ index had a significant negative relationship with the values of urban physical environment indexes. Spatially, the green space density showed a completely significant correlation with GHQ index.

The present study demonstrates the hypothesis that the design of an urban environment is significantly related to the GHQ of citizens. The results emphasize that increasing the density of local ground commercial space, land use mixing ratio, more roads connectivity by increasing the walk-ability index and especially the development of green space are among the interventions that can improve the GHQ.

Climate change is the greatest price society is paying for decades of environmental neglect. The impact of global warming is most visible in the rising threat of climate-related natural disasters. Globally, meteorological disasters more than doubled, from an average of forty-five events a year to almost 120 events a year (Vinod, 2017). Climate change refers to changes in the distributional properties of climate characteristics like temperature and precipitation that persist across decades (Field et al., 2014). Because precipitation is related to temperature, scientists often focus on changes in global temperature as an indicator of climate change. Valipour et al. (2021) reported the mean of monthly the global mean surface temperature (GMST) anomalies in 2000–2019 is 0.54 C higher than that in 1961–1990. Many studies have been done on climate change in Iran. These studies have mostly studied the mean and extreme temperature trends (Alijani et al., 2011; Masoudian and Darand, 2012). In general, the results of previous studies showed that the statistics of mean, maximum and minimum air temperature in most parts of the Iranian plateau have increased in recent decades. Also, the increase of minimum temperature is greater than maximum temperature. A review of the research background shows that we need to understand more about regional climate change in Iran. Therefore, present study performs the climate change of 14 extreme temperature indices using multivariate statistical methods at the regional scale.

Historical climate observations including daily maximum and minimum temperature were obtained from the Iranian Meteorology Organization for the period 1968 to 2017 at 39 stations. In this paper, 14 extreme temperature indices defined by ETCCDI were analyzed. The indices are as follows: (1) Annual maxima of daily maximum temperature (TXx); (2) Annual maxima of daily minimum temperature (TNx); (3) Annual minima of daily maximum temperature (TXn); (4) Annual minima of daily minimum temperature (TNn); (5) Cold nights (TN10p); (6) Cold days (TX10p); (7) Warm night (TN90p); (8) Warm day (TX90p); (9) Frost days (FD); (10) Icing days (ID); (11) Summer day (SU); (12) Tropical nights (TR); (13) The warm spell duration index (WSDI) and (14) the cold spell duration index (CSDI). The extreme temperature indices were extracted using R software environment, RclimDex extension. The Mann–Kendall Test and Sen’s Slope Method was employed to assess the trends in 14 extreme temperature indices. To identify homogeneous groups of stations with similar annual thermal regimes, Principal Component analysis (PCA) and Clustering (CL) was applied. Pearson correlation coefficient was used to investigate the relationship between height and trend slope.

All the extreme temperature intensity indices (TXx, TNx, TXn, and TNn) showed increasing trends during 1968 to 2017. The increasing trends of TXx, TNx, TXn, and TNn were 0.2, 0.3, 0.44, and 0.5 ° C per decade, respectively. These results indicated that the extreme warm events increased and the extreme cold events decreased. The average of the extreme temperature frequency indices over Iran showed that the frequency of warm night (TN90p) and warm day (TX90p) significantly increased with a rate of 6.9 and 4.2 day per decade, respectively. Also, the frequency of cold night (TN10p) and cold day (TX10p) significantly fell with a decrease rate of 3.8 and 3.8 day per decade, respectively. The frequency of warm nights (TN90p) was higher than that of warm days (TX90p). The result indicated that the trend of nighttime extremes were stronger than those for daytime extremes. The average of frost days (FD) and icing days (ID) indices over Iran showed decreasing trends during 1968 to 2017 with rates of 3 and 1.1 d per decade, respectively. While, the averaged of summer days (SU) and tropical days (TR) indices over Iran showed increasing trends with rates of 4.4 and 6.4 day per decade, respectively. The warm spell duration index (WSDI) indices showed a clear increase, with a rate of 2.1 per decade. In contrast the cold spell duration index (CSDI) showed a significant decrease, with a rate of 1.7 per decade. In general, the cold indices displayed decreasing trends, whereas the warm indices displayed increasing trends over most of Iran. Pearson correlation coefficient between height and Sen’s Slope was estimated to be equal to -0.62 (p < 0.01). In general, the results of this study showed that there is a negative correlation between the elevation factor and the Sen’s Slope of warm extreme indices. That is, as the altitude decreases, the Sen’s Slope increases. Therefore, the stations located in low altitude have experienced stronger increasing trends than in high altitude. The area of ​​Iran was classified into four clusters using PCA and CL methods. Cluster 1 has experienced the strongest increasing trends. The average height of cluster 1 is 535 meters. Approximately 38% of the studied stations were located in cluster 1. Cluster 2 showed a moderate heating trends. 33% of the stations were located in cluster 2. Most of the stations of cluster 2 are located in the northwest and west of Iran. Cluster 3 showed a weak increasing trends compared to clusters 1 and 2. The stations of cluster 3 did not show a special geographical concentration and were scattered in all parts of Iran. 18% of the studied stations are located in cluster 3. The stations of Cluster 4, have experienced weak decreasing trends, which was different from the other three clusters

In this study we analyzed the climate change of extreme temperature indices in Iran. The result showed that the frequency of warm nights, warm days, summer days and tropical days increased. Also, the frequency of cold nights, cold days, Frost days and icing days decreased. The warm spell duration index showed a clear increase. In contrast the cold spell duration index showed a significant decrease. In general, the extreme warm events increased and the extreme cold events decreased over most of Iran. There is a negative correlation between the elevation factor and the Sen’s Slope of extreme warm indices (R = -0.62). Therefore, the stations located in low altitude have experienced stronger increasing trends than in high altitude. The area of ​​Iran was classified into four clusters using PCA and CL methods. Cluster 1 has experienced the strongest increasing trends. The average height of cluster 1 is 535 meters. Therefore, the most heating have occurred in Low-lying areas of Iran. Cluster 2 and Cluster 3 showed a moderate and weak heating trends, respectively. The stations of Cluster 4, have not experienced clear trends.

Abstract In this paper, the probability of drought and wet year occurrence in Tehran by applying the first-order Marcov chain on Standardized Precipitation Index (SPI) time series in the scales of 6, 9,12,24 and 48 month were investigated. For this purpose, we used the monthly precipitation data of the Mehrabad station from January 1950 to December 2006. After that, SPI were computed in mention scales. Then, the conformity of SPI time series to the first-order Marcov chain were tested statistically by test statistic X2 and also confirmed. In the first of all, transition probability of drought, wet year and normal state were computed. In addition to, middle number of drought and expected wet year for future were forecasted. The result showed that transition probability of every state to its is more than other states. The probability of Pdd (the probability of drought after drought) is more than Pww (the probability wet state after wet state). Whatever, the time scale of SPI become longer, its stability is increased. On the whole, the probability of normal state is the most among all and the drought equilibrium probability is more than wet year. whatever time scale of SPI became longer, the number of drought is decreased and its duration is increased. In the of all, occurrence probability of drought is more than wet year.

In this study, Landsat TM images were used to analyze the spatio-temporal changes of urban heat island of Tehran. The time period of images (13 images) is from 1986 to 2010. First, the mono-window algorithm was utilized to retrieve land surface temperature (LST) from thermal band of Landsat TM images. Then, the global and local spatial autocorrelations are used to quantitatively explore the spatial and temporal evolution of LST in Tehran. Results of global spatial autocorrelation showed that LST field in Tehran has changed to cluster pattern during the study period. In addition, the rate of global spatial autocorrelation increased from 1986 to 2010. According to the results of the global spatial autocorrelation two important remarks were obtained: (1) new thermal clusters were created during the study period. (2) The spatial extent of the old thermal clusters have been increased. To clarify the nature of the clusters (hot or cool cluster) and to explore the spatial variations of these clusters, the local spatial autocorrelation were used. These results confirmed the strengthening and extension of the hot clusters and weakening of the cool clusters. Exploration and Comparison of the spatial distribution of the high-high and low-low points during the study period showed that between 1986 and 2010 due to the degradation of half of the vegetation in the west and southwest of the Tehran (Districts of 18, 19, 21 and 22) cool clusters have been disappeared or fragmentized and new thermal clusters formed. As a result of these changes, urban heat island that was dominant in Mehrabad Airport (District 9) and portions of Districts 21 and 22 in 1986 expanded toward the west and southwest. Also, small thermal cluster have been emerged in the south and west of District 19. Moreover, because of the degradation of orchards in the northern part of Tehran (especially Shemiranat) cool clusters of these Districts have been weakened.

Urbanisation changes the land cover types in urban areas and results in different climatic conditions، which has been termed as “Urban climate”. Urban climates are different from those of less built-up areas in terms of air temperature، humidity، wind speed and direction، and amount of precipitation. The previous researches show that urban areas are warmer than surrounding rural areas creating the «urban heat island» (UHI) (Rose and Devadas; 2009، 2). The buildings، concrete، asphalt and industrial activity of urban areas causes UHI. Replacing natural land cover with pavements، buildings and other infrastructures takes away the natural cooling effects. Also، tall buildings and narrow streets can heat the air trapped between them and reduce airflow. In addition، heat from vehicles، factories and air conditioners adds heat to the surroundings، further exacerbating the heat island effect. UHI can impact local weather and climate، altering local wind patterns، spurring the development of clouds and fog، increasing the number of lightning events، and influencing the rates of precipitation. Furthermore، the poor air quality that results from the increased energy usage for cooling purposes in heat-island city can cause discomfort for humans and affect health، aggravating asthma and promoting other respiratory illnesses (Liu and Zhang، 2011:158). Thermal remote sensing data play an important role in the study of UHI. First، UHI is studied using NOAA AVHRR thermal data (Balling and Brazell، 1988:1289-1293; Gallo et al.، 1993:899-908; Gallo and Owen، 1988:159-172; Streutker، 2002:282-289). Later، thermal infrared data TM، ETM+ and ASTER are used to study UHI more precisely (Weng، 2001:1999-2014; Weng et al.، 2006:1275-1286; Amiri et al.، 2009:2606; Flahatlar et al.، 2011). Meanwhile، in some studies، The spatial and temporal variations of UHI are detected by using multi- temporal thermal images of landasat TM and ETM (Mo et al.، 2011:4616-4622). Several researchers (Akbari، 1379; jangi، 1383; shakiba et al.، 1388:56-69; namdari، 1388; malekpour and taleai، 1389:89-102، and 1390:29-42) have studied the UHI in Tehran. But none of them have presented a comprehensive picture of its spatial and temporal variations. Thus، the main objective of this study is to study the spatial and temporal variations of UHI in Tehran urban area. Study Area: The city of Tehran as capital of Islamic republic of Iran is located between latitudes of 35°33’10“N to 35°50’12“N and longitudes of 51°05’17“E to 51°37’36“E with an average elevation of 1600 m، is surrounded by high mountains in the north and north east. Tehran experiences warm summers and cold winters. Tehran is a major center of culture، industry، commerce and transportation. The biggest city of the country، Tehran exhibits rapid population growth and urban expansion in the form of encroachment to the limited agricultural areas (malekpour et al.، 2010). Due to its complicated expansion and urban structure and function the temperature variations are very important for its life and existence. Thus this study has tried to analyse the spatial and temporal variations of its temperature. In this paper، multi- temporal Landsat TM images (13 images) are used for the analysis of UHI in Tehran. LST is extracted using the mono-window algorithm presented in Qin et al (2001). Then، using appropriate statistical methods، spatial and temporal variations of LST were analysed. Based on thermal radiance transfer equation، the mono-window algorithm only requires three parameters of emissivity، transmittance and effective mean atmospheric temperature - to retrieve LST from Landsat TM 6. The spatial model to retrieve LST from Landsat TM using ERDAS spatial model tool is designed. In this model، only two measured parameters are required; near-surface air temperature and water vapour content of the atmosphere at the time of satellite pass، which can be easily obtained from synoptic weather stations of Tehran. These two parameters are then converted to air transmittance and effective mean atmospheric temperature. The third required parameter is the emissivity، which can be calculated from the normalised difference vegetation index (NDVI). The remaining useful data can all be obtained from the Meta file in the satellite image data. It is impossible to compare thermal data from different years directly using absolute LST. Therefore، a normalisation technique (Xu et al.، 2009) has been used to compare the computed LST of different years. The LST images were rescaled to the same level between 0 and 1 using the maximum and minimum values for those images. Then temporal variations were explored. The intensity of UHI from 1986 to 2010 was evaluated by the urban heat island ratio index (URI) (Mu et al.، 2011). The URI was proposed to quantitatively compare the UHI differences in different years based on the ratio of UHI area to whole city area. The temporal changes of LST during the study period showed that the distribution pattern of LST has changed. The area of moderate and very cool temperature of the city has been decreased but the area of very high temperatures (very hot areas) has been increased significantly. It is completely clear that spatial extent of UHI along with the spatial development of Tehran have been increased during this period of 25 years (1986 to 2010) and the extent of UHI has increased from 83 square kilometres (13 percent) to 99 square kilometres (16 percent). The temporal change of the intensity of UHI also showed that URI has increased. The URI has increased from 0. 11 in 1986 to 0. 15 in 2010. According to the spatial distribution of LST، UHI has maintained its principal center (Mehrabad airport) and The new hot clusters have emerged in the west (District 21 and west of district 22) and south- west (portion of District 18 and 19) of the Mehrabad airport. Our study showed that UHI of Tehran has extended toward the areas with an intensive decrease in vegetation and the extensive development of industries، working places and warehouses (the west and south-west of Tehran). In this study، the mono-window algorithm is applied to retrieve LST in Tehran using the Landsat TM data. Then، using appropriate statistical methods، spatial and temporal variations of LST are analysed. Consideration of spatial-temporal variation of LST during the study period showed that the distribution of the UHI in Tehran has changed. Center of the UHI that had already been located on Mehrabad airport has extended toward the west and southwest of Tehran. The metropolitan of Tehran has witnessed a very fast urban sprawl during the study years from 1986 to 2010. The urban expansion was accompanied by increased UHI intensity of 0. 11 in 1986 to 0. 15 in 2010 over an almost 25-year period and resulted in the development of the severe UHI in the region and thus the degradation of the liveability of the city.

In order to analysis short-term wet and dry periods and predict the occurrence probability of wet periods in 1 to days in the several climatic areas of Iran¡ the rainy days with 0.1 mm and more for 30 years (1976-2005) at 9 selective station were investigated by applying the tow-state¡ First-order Marcov chain. The important features in relation to short wet and dry periods as well as conditional and climatic probabilities¡ day¡ s abundant¡ the length of wet and dry periods and eventually the occurrence probability of 1 to 6 day periods were recognized. In all of these stations under study¡ the most abundant percentage of wet days occurs in winter and decrease in spring and autumn and the amount of reduction intensifies in the stations in the south¡ south eastern and central area of Iran. The maximum transition probability of two successive wet day (P11) occurred in Rasht¡ Khorramabad and Tabriz and the minimum P11occures in Zabol¡ Yazd and Bandarabbas. The more we move from the north and west to the south eastern of Iran¡ the more the climatic probability of wet periods (π1)¡ the length of wet period (E1) and the frequency of rainfall 1 to 6 days decreases and in the other hand duration of the weather cycle (Ec) increases. In all of station¡ the occurrence probability of one-wet-day is more than others and the more duration of wet period’s increases¡ the occurrence probability of them decreases.

In order to identify the spatial relation between the subtropical high pressure system with summer rainfall in the southern half of Iran, the data about the daily rainfall of synoptic stations of the southern half of Iran were examined from 1987 to 2005 thus six widespread raining periods were selected in this regard. After exploring the ground level pressure map and the geopotential height maps at levels of 300, 500 and 700 hpa throughout the selected rainy days, two different patterns were detected. In the first pattern, the moisture of the Indian ocean and the contiguous seas transfers to the low level of troposphere as a result of monsonal cyclonic movement system. In the median levels, the western trough has expanded towards the southern half of Iran and resulted in the recoil of the subtropical high pressure toward the lower latitude. In addition, the subtropical high pressure axis places in the western-eastern manner. Throughout the rainfalls in this model, the maximum decrease in geopotential height occurs at 300 and 500 hpa respectively and continues into the median levels of the convection layer due to dwindling subtropical system. In the second pattern, the monsoon system has directed toward our area of investigation and severe rainfalls took place as the monsoon systems approached. In this model, the western streams trough have expanded toward the Mediterranean basin and results in the recoil of the subtropical high pressure flow toward the northern part of Africa, out of which a high pressure core is separated and located on Iran. In this situation, the high pressure system transfers to the upper levels also,the condition for mansoon wet stream elevation and convectional rainfalls has been provided. In this model, the maximum decrease in the geopotential height has occurred at 700hpa and the thickness of the convection layer is lower than the first model which would reach to 700 hpa level.