فهرست مطالب تقی طاوسی

Today, the adverse effects of climate change and the resulting damages have become an environmental, social and economic problem. Evaluating the resilience of local communities against climate change and its limitations and obstacles is an important step for identifying effective mechanisms and prioritizing management that promotes flexibility and increases adaptation capacity. Due to the importance of this issue, the current research aims to identify the limitations of coping. and resilience against the risks caused by climate change was carried out in Zahedan city. The current research is applied in terms of purpose and its method is descriptive-analytical. The tool for collecting data and information was a researcher-made questionnaire from the study area. The statistical population was the rural households of Zahedan city, which due to the dispersion of villages and their large number, 12 villages (2 villages from each village) were randomly selected as sample villages. According to 832 households of the studied society and using Cochran's formula, the sample size of 263 households was obtained, which was increased to 265 households. In order to analyze the data, ISDM method was used in SPSS software and structural equation method in LISREL software. The results showed that 12.83% of residents have weak perception, 23.02% have moderate perception, 35.85% have strong perception and 28.30% have very strong perception of climate change. Also, the physical factor (factor load 0.941), social factor (factor load 0.922) and economic factor (factor load 0.895) are the most important limitations of resilience against the risks caused by climate change in Zahedan city.

This article attempts to examine the appropriate time for tourism in the cities of Sistan and Baluchestan province, based on the physiologic equivalent temperature index (PET). The PET index is one of Rayman's software outputs, which is used to explain the tourism climate in Zahedan, Khash, Saravan, Zabol, Iranshahr and Chabahar cities. First, daily data (10957 days), air temperature, cloudiness, water vapor pressure, wind speed and relative humidity of meteorological stations of these cities were collected (1986-2015). The results of RayMan inferred in the form of daily climatic calendars. According to the monthly percentage of non-stress days (thermal comfort), the results showed in Apr (Zabol and Iranshahr, 67%), May, June, Jul and Sept (Zahedan, 28-90%), Oct (Saravan 87%), Nov (Iranshahr 87%), Des, Jan, Feb and Mar (Chabahar, 42-95%) have the best conditions for the presence of tourists. The best conditions for tourism in Zahedan (May and Sept), Khash (May, Sept and Oct), Saravan (Apr and Oct), Zabul (Apr and Sept), Iranshahr (Apr and Nov) and Chabahar (Dec, Jan, Feb, Mar and Apr) are estimated to have the highest percentage of non-stress temperature days.

Projection of summer monsoon rains in Southeast Iran based on Ensemble model the precipitation factor has a variable and random nature and has a different behavior in terms of space and time. Therefore, the prediction of precipitation has more uncertainty compared to other meteorological variables. In the current study, the data output of Cordex database and CMIP5 models were used using the neural network method to reduce the uncertainty and estimate precipitation properly. The results showed that due to the high correlation of temperature, humidity and air pressure with precipitation, the use of these variables is beneficial in reducing the uncertainty of precipitation forecast. In addition, the non-linear method of artificial neural networks can be used to bias the rainfall data of Cordex database and CMIP5 to forecast the rainfall in the southeast of the country. Another result of this research is the increasing trend of rainfall in the southeast of Iran, especially in the coastal areas. This can be considered as a result of the increase in the level under the influence of rains affected or simultaneous with the southwest monsoon of India. The increasing trend of precipitation in the southern coasts is also related to the increase in the storage capacity of moisture content. The interannual variability of India's monsoon rainfall also shows a steady positive trend under continued global warming. Since both the increase in the duration of monsoon rains and the increase in interannual variability in the future are seen in most models, we can be confident in these predicted trends. Indian summer monsoon rainfall is also predicted to be higher under global warming in the 2050s compared to the baseline.

The present study aims to investigate the frequency distribution of monthly, seasonal and annual temperature in the boundary layer of Shiraz. For this purpose, radiosonde data downloaded at 3.5 local time during 1394 -1380 (5478 days) from the University of Wyoming web site. Then, the height of the meteorological station of Shiraz (1491 m) was determined as the base level of the inversion of the boundary layer of air, and The Top of the Inversion layer was selected to the geopotential surface of 700 hp (an average of 1.5 km from the lower layer above the surface) as the study space. The results showed that October and November are the highest and July's low frequency of inversion days. On this basis, the autumn, winter, spring and summer seasons were the most days of inversion, respectively. Also, the results on the annual scale showed that the frequency of inversion days was increasing. As the average monthly increase in the frequency of inversion days, the air temperature in the first 5 years (1390 -1394) compared to the first 5 years (1385 -1389) was twice as high as 5 years in comparison with the first 5 years (1380 -1384). The annual average annual average also showed that 73% of the year (267 days) of Shiraz was faced with inversion phenomenon. The most intense inversion of temperature in the air interface have occurred in January, this clearly demonstrates the role of night cooling in the intensification of inertia of the temperature of the boundary layer of the air .

The climatology of Thunderstorms is an important component in research for severe weather. Thunderstorms are among the first meteorological phenomena, which have attracted human attention (Khorshiddoust et al, 2017). Thunderstorms are dangerous and one of the most important, abundant and severe atmospheric hazards. Thunderstorms can be associated with a number of hazards. This phenomenon is associated with severe storms, showery precipitation, hail, and thunder and lightning. Heavy rains can lead to flash flooding events. High winds generated by thunderstorm can cause damage to homes, overturn vehicles, uproot or damage trees, causing wide spread power outages. Generally, researchers consider the intense weather instability as a result of convection in lower levels of the atmosphere with high levels enough of humidity. Usually statistic instability, the humidity of lower levels of the atmosphere and lifting mechanisms near the ground are the main factors leading to convection. Moreover, the combination of three factors, instability, humidity and convergence in lower levels of the atmosphere plays an important role in increasing the possibility of thunderstorms (Masoompour Samakosh et al, 2016). In connection with thunderstorms extensive research work has been carried out in Iran and the world in including: Chignon et al. (2001), Manzato, (2003), Doswell et al. (2005), Henderson (2006), Sadeghi et al. (2006), Romero et al. (2007), Schmeits et al. (2008), Siedlecki (2009), Sanaeinejad et al. (2010), Tajbakhsh et al. (2010), Ghavidel Rahimi (2011), Masoompour Samakosh et al. (2014)  Masoompour Samakosh et al. (2016), Tavousi (2016), Dehani (2017), Khorshiddoust et al. (2017), Tavousi  et al. (2016).The city of Kermanshah is the capital of the Kermanshah province and is located in the west of Iran. The latitude of the Kermanshah meteorological station is 34: 21 N and the longitude is 47: 9 E and altitude 1318.6 meters. Kermanshahchr('39')s climate is classified as warm and temperate. The winters are rainier than the summers in Kermanshah. The climate here is classified as Csa by the Köppen-Geiger system. The average annual temperature is 13.3 °C in Kermanshah. The average annual rainfall is 437 mm (Climate data for cities worldwide, 1982-2012). Kermanshah has annually been witnessing a variety of thunderstorms systems and associated precipitation. This city has suffered lots of damage resulted from the phenomena caused by thunderstorms.

In this research, instability conditions of heavy precipitation in Kermanshah are investigated. For this purpose, high atmospheric instability indices such as lifted index, showalter index, K index, convective available potential energy (CAPE) index, precipitable water capacity (PWC) and thermodynamic diagram Skew-T Atmospheric is studied using the radiosound data. The data of upper atmosphere (radio-sound data), available in the website of Wayoming University, were applied to investigate the thermodynamic features of the occurred thunderstorms. The thermodynamic features include KI, SI, TT, LI, CAPE indices and skew- T chart in RAOB software.

The results showed that the valuses of K index in days with heavy precipitation were 20.7-34.8 and in a day before 20.9 - 37.7. The lowest values recorded in January, February and March, and the peaked were in November, April and May. This suggests heavy precipitation in winter with less instability and is accompanied by more instability in the fall and spring. The lifted index in 1997 and 2002 in days has heavy precipitation were 0 to -2.2, which represents the probability of storms with rain and snow showers. The value of the lifted index in a day before precipitation on November 1, 1993 was zero to -2 and on May 12, 1993, November 21, 1994, and April 18, 2002 from -2 to - 5, which represents the probability of thunderstorm occurring. Study of precipitable water capacity (PWC) in the peak days of precipitation and one day before is showed that is most matches with the days that air convection has been intense. On peak precipitation days, the PWC was between a minimum of 35/7 on16 January 1997 and a maximum of 19.92 on 2 November 1993. The wind speed has been between 40-50 knots in all days, except on March 11, 2005, the wind had a speed of about 80 knot. The Prevailing winds are southwest which shows the direction of the Westerly winds system to this area. Investigation of thermodynamic charts showed that rapid convective ascent of available potential energy depending on the weather in the region has been so high and caused the weather to approach three days in advance to the upper layers of the atmosphere and atmospheric turbulence was created for the region.

The climate of the planet is being changed, and its major consequences are directed towards the coastal areas, especially the coastal cities. On the other hand, using the output data of climate models requires evaluating its accuracy against observational data. The purpose of this research was to evaluate the accuracy of CMIP6 climate models in Makran coast. In order to investigate the future climate conditions in the coast of Makran, 11 Climate models were used in evaluation of the CMIP6 output during the period of 1985-2014. Two synoptic stations of Makran coast (Chabahar-Jask) were used. The observational meteorological data were the sum of monthly rainfall, monthly average parameters of air temperature, air humidity, maximum temperature, minimum temperature, wind speed and air pressure of two synoptic stations of Chabahar and Jask, which were evaluated with the corresponding data of the determined models. The results showed that precipitation, wind and humidity had very weak correlations and cannot be a suitable criterion for model selection. But the set of average, minimum and maximum temperatures as well as air pressure had sufficient correlation. Nash-Sutcliffe .normalized root mean square error and Kling-Gupta indices also confirmed these results. According to the mentioned investigations and calculation results, six models including FGOALS, MPI-ESM1, CanESM5, MRI-ESM2, EC-EARTH3, IPSL-CM6A, ACCESS-ESM were selected as the best models among the 11 models determined at the beginning of the research. Thereafter, an ensemble model was introduced using arithmetic mean and independence weighted mean (IWM) method, and the weighted mean model showed better results.

The problem of drought and water crisis in the in the central Iran watershed has become serious in recent years due to consecutive droughts and increased water consumption in drinking, agriculture and industry sectors. Since rain is the only source of water supply in this catchment area, a decrease in the amount of rainfall with this intensity can cause a widespread drought and eventually large migrations from these areas. Therefore, the aim of this research is to analyze the changes in the aridity index in the vast area of the central Iran watershed in future.

In order to achieve the study's objective, the minimum and maximum air temperature, sunshine hours, and precipitation of 40 synoptic stations in the Central Iran watershed for a period of 20 years (1991-2010) were received from the Meteorological Organization.Then the values of potential evapotranspiration, aridity index, and Angot precipitation index were calculated for each station in the current conditions. In order to project changes in the aridity index in the future, the output of three MIROC5, HadGEM2-ES, and GFDL-CM3 models for the historical period (1991–2010) and the medium future (2041–2060) under the RCP4.5 scenario and based on the LARS- WG6 scaled down. After evaluating the accuracy of the models against the observational data, the index values were calculated in future conditions, and zoning maps were drawn for the study area.

Projection of changes in evapotranspiration values under the RCP4.5 scenario (2041–2060) showed that the most changes were in January, March, December, and November. Shahrekord showed the highest percentage of incremental changes, with 36.8% change in January compared to the base period. In terms of rainfall regime, the Central Iran watershed has a winter rainfall regime based on the Angot precipitation index in the current conditions. The HadGEM2-ES model is consistent with the base period, but based on the MIROC5 and GFDL-CM3 models, the winter precipitation in many stations will change to the all-season precipitation regime in the future. Climatic zoning of the UNEP aridity index in the studied area indicated that in current conditions, more than half of the stations have a dry climate. Only Kohrang has a humid climate with an aridity index value of 0.78. Shemiranat and Oligoders have semi-dry conditions with values ​​of 0.21 and 0.20, respectively. The evaluation of the future climate conditions according to the GFDL-CM3 model shows that the humid climate in central Iran will gradually disappear, while the semi-arid climate will expand in this region. The output of the MIROC5 model also shows the expansion of the ultra-arid climate zone in different parts of the catchment area of Central Iran.

The results showed that the aridity index values based on selected GCM models have decreased in the studied area compared to the observation period. Therefore, a large number of stations that have dry conditions in the base period will experience ultra-dry conditions in the future climate.The evapotranspiration potential in the Central Iran watershed is increasing during all months of the year, especially in wet stations in the west. This issue shows the dominance of the aridity index over this region in future conditions.

This research aimed to analyze the awareness, attitude, and ecological behavior of citizens in Ᾱbādān in dealing with harmful ultraviolet radiation. A library method was used to identify the relationship between climate parameters and ultraviolet index, while a field method and questionnaire were employed to analyze the ecological behavior of citizens towards ultraviolet hazards. The statistical population included all citizens of Ᾱbādān, and the sample size was determined to be 384 using Cochran's formula. The validity of the questionnaire was confirmed through a pre-test and then completed through random sampling. Monthly averages of maximum, minimum, and average temperature, precipitation, relative humidity, cloudiness, sunshine hours, and ultraviolet radiation index (1951-2017) were obtained from the Ᾱbādān meteorological station. After estimating the monthly potential evaporation and transpiration, calculating the UNEP drought index and the Angot rainfall index, and plotting climatic diagrams, the Pearson correlation coefficient and the coefficient of determination were used to examine the relationship between each of these factors and the ultraviolet index. The correlation coefficient between the ultraviolet index and relative humidity (-0.95) and cloudiness (-0.87) was found. The function (RSQ) also indicated the higher role of relative humidity (0.89) compared to cloudiness (0.76) in reducing the ultraviolet index. The Kruskal-Wallis test indicated a significant difference in the level of awareness among the study groups in Ᾱbādān regarding awareness, education, attitude, and preventive measures. The results indicated that the level of awareness and education among citizens regarding harmful ultraviolet radiation is moderate, while they have a very high attitude towards this environmental issue and were somewhat familiar with preventive measures.

Drought has imposed a huge damage to country’s economy especially in recent decades. Pasture yield losses, reduction of agricultural and drinking water, reduction of groundwater and surface water resources, outbreak of plant and animal pests and diseases and an increase in migration are among the negative effects of drought. The aim of this research is understanding atmospheric circulation patterns with modern methods and based on further data; therefore in case of synoptic patterns identification associated with drought and wet years, these patterns can be used to forecast country’s wet and dry periods with a very high accuracy.

To identify and extract widespread Iran’s droughts and wet years and in order to achieve the objectives of the research, two databases were required: Surface environment data and upper atmosphere data. Surface environment data was used from rainfall data of 43 synoptic stations in a 33-year period (1976-2009) which was received from the Iran Meteorological Organization. High atmospheric variables which were used in this research include: Geopotential height, sea level pressure, zonal wind, meridional wind, air temperature and specific humidity. Data and maps of all these variables were collected from www.esrl.noaa.gov/psd website as monthly data. Data related to Geopotential height variables; zonal wind, meridional wind and the air temperature at 17 levels and specific humidity in 8 level data are available. A suitable index was selected in order to analyze inclusive droughts and wet years of Iran, so droughts and wet years could be separated according to it. In this research Standardized Precipitation Index (SPI) was selected given its advantages compared to other drought indexes. Synoptic analysis method of patterns related to Iran’s monthly inclusive droughts and wet years, were divided into three categories based on a principle location: local droughts (or wet years): Droughts (or wet years) which declared about 25% and less of studied stations in Iran’s droughts (or wet years). Semi-inclusive droughts (or wet years): Droughts (or wet years) which declared about 25 to 75 percent of studied stations in Iran’s droughts (or wet years). Inclusive droughts (or wet years): Droughts (or wet years) which declared about 75% and more of studied stations in Iran’s droughts (or wet years).

The results showed that in the inclusive droughts, positive temperature anomalies and in inclusive wet years, negative temperature anomalies can be observed in Iran. Composite maps of humidity anomalies also nicely demonstrate that in the times of drought across Iran, negative anomalies have been found and in the wet years contrast status of droughts have happened and the positive anomaly got over Iran. In the months that inclusive drought happened in Iran, it can be seen that European and Asian high pressure combined together and put the whole of Europe and Asia under domination which under these conditions, Iran experienced drought months as during this time cyclonic circulation formed on the Arabian Sea which made humidity of the Arabian Sea not to transferred to Iran. The second affecting anomalies on this phenomenon, is the Mediterranean Sea; in these months a major anti-cyclonic circulation dominated on Europe. This major anti-cyclonic circulation affected Mediterranean Sea and even North Africa. In these circumstances Mediterranean cyclone formation was disrupted and so no humidity transferred to Iran. When European high pressure move to the North Atlantic Ocean and provide space for the establishment of a polar low pressure on Europe; in these circumstances regional low pressure is formed on Mediterranean Sea which causes more humidity entering Iran which results will be wet months; as well as Anti-cyclonic circulation ruling on of the Arabian Sea that crosses over the Red Sea is causing humidity injection in Iran.

In the months that inclusive drought happened in Iran, it can be seen that European and Asian high pressure combined together and put the whole of Europe and Asia under domination which under these conditions, Iran experienced drought months as during this time cyclonic circulation formed on the Arabian Sea which made humidity of the Arabian Sea not to transferred to Iran. The second affecting anomalies on this phenomenon, is the Mediterranean Sea; in these months a major anti-cyclonic circulation dominated on Europe. This major anti-cyclonic circulation affected Mediterranean Sea and even North Africa. In these circumstances Mediterranean cyclone formation was disrupted and so no humidity transferred to Iran. When European high pressure move to the North Atlantic Ocean and provide space for the establishment of a polar low pressure on Europe; in these circumstances regional low pressure is formed on Mediterranean Sea which causes more humidity entering Iran which results will be wet months; as well as Anti-cyclonic circulation ruling on of the Arabian Sea that crosses over the Red Sea is causing humidity injection in Iran.

Public open spaces in residential areas of cities are one of the fields for the social interactions. Hence, the climatic and geometric characteristics of urban open spaces must be harmonious and facilitate social relations. This is doubly important, especially in hot and arid environments. The purpose of this study is to investigate the thermal comfort of urban open space and its influential components in strengthening social relations in the old neighborhood of Quds neighborhood in Zahedan.

The present paper is applied in terms of purpose and experimental-correlation in terms of method. To evaluate the thermal comfort of the outdoor spaces, physiologically equivalent temperature (PET) and predicted mean votes (PMV) based RayMan model and universal thermal comfort index (UTCI) based on BioKlima model have been used. A new mathematical model is then proposed based on the correlation relations between environmental variables and individual subjective responses. Field studies including measuring meteorological parameters, thermal environment perception, and geometry of urban open space are the final part of this research.

Findings showed that the time range of urban outdoor thermal comfort in Quds neighborhood is abundant in the afternoon in summer. The afternoon microclimate is dependent on the fabric of the neighborhood and has the potential to enhance social interactions. The proposed mathematical model for estimating thermal comfort in hot and arid environments based on the correlation of environmental variables and actual sensation vote (ASV) is well able to express an actual thermal sensation of outdoor spaces.

Therefore, in order to take the necessary measures to develop and promote the social interactions of the neighborhood, physical infrastructure such as outdoor furniture development and neighborhood social institutions should be strengthened. The results of these measures can reduce the urban social harms.

In this study, the average climate data of meteorological stations including temperatures of the warmest and coldest months of the year, precipitation regime, potential evapotranspiration and UNEP aridity index has been used to map Iran's climate zones. In this regard, climate variable of air temperature, relative humidity, potential evapotranspiration, and precipitation characteristics of 303 meteorological stations throughout Iran was used on monthly and annual time’s scales. The annual aridity index in each site was calculated using the United Nations Environment Program (UNEP) index. Then, the temperature characteristics of the warmest and coldest months of the year were coded. Results show a very high climatic diversity throughout Iran. In this model, Iran's climate was divided into 27 categories. Based on aridity index, Iran has seven climates zones. There are 30 cities with hyper-arid climate. This climate type has three climate territories and occupies about 3.4 percent of the country's territory. The arid zone with five climate territories cover about 23.7 percent of the country and dominates 95 cities. The semi-arid climate with 6 climatic territories accounts for about 39.6 percent and dominates 113 cities. The dry sub-humid zone with four climate territories and covers about 17.3 percent and dominates 30 cities. Nine cities have a semi-humid climate with three climatic territories which accounts for about 8.9%. The humid climate with four climate territories covers about 5.8 % and dominates 13 cities. The very humid climate with 2 climatic territories accounts for about 1.3% and represents the climate type of the 12 cities.

South East of Iran will yearly receive part of its water requirements from the summer precipitation, which is mostly due to the monsoon expansion. These precipitations are related to the temperature changes in the Indian Ocean level (Aramash et al., 2016: 2). Producing the accurate climate data is one of the main goals of the forecasting and modeling centers. Among the most important advantages of this data can mention the following: better estimation of the climatic variables in the regions which have no station, possibility to study the climate more appropriately and evaluate the fluctuations and changes of climate elements (Forsythe et al., 2015).

In this research, we used daily precipitation data of 6 synoptic stations and the outputs of various CORDEX models in the South Asia during the statistical period of 30 years (2005-1976) in the studied region.

Evaluation of the accuracy of the global models' output on the basis of the downscaling of the studied regional model on a daily basis during the monsoon period (June, July, August and September) in (1976-2005) indicated that according to the different indicators the CanESM2, CSIRO and NorESM1 models have respectively more accurate estimation of precipitation values at most studied stations than other models. The correlation coefficient of none of the models has a good relationship. The observed and estimated precipitation values of the studied models in the form of the average activity months of the monsoon system showed the accuracy of the investigated models at each station is different but, in general, the three models CanESM2, CSIRO and NorESM1 are more appropriate in the estimation at the most stations than other models. A number of macro criteria must be considered to select the proper model; the 500 HPA Geo-potential height and the sea level pressure have been used in this research for this purpose. In fact, investigating the model's ability to simulate the 500 height as well as the earth is preferable over precipitation and temperature.

The results have suggested that the accuracy of the studied models at a variety of stations is different but, totally and at most of the stations, the three models CanESM2, CSIRO and NorESM1 have respectively better estimation of monsoon precipitation values than the other models. We cannot definitely prefer one model over the others according to the error estimation criteria as well as the comparison of different models with each other. We have shown in this research that the large scale variables such as Geo-potential height and pressure are more predictable than the precipitation and CanESM2, CSIRO-Mk, IPSL-CM2A-MR, MIROC2 and MPI ESM-LR models can be introduced as suitable models to simulate and predict climatic parameters of sea level pressure and 500 HPA Geo-potential in the monsoon system activity governing on the South East of Iran.

Short-term prediction of minimum temperature is important in mitigation chilling and frost injury in agriculture. In current study, the frequency of early autumn and late spring frosts in Sanandaj synoptic station, Iran were worked out. Then, using six variables, i.e. dry and wet bulb temperature, relative humidity, wind speed, wind direction, and cloud cover as the inputs, a multilayer perceptron artificial neural network model (MPL/ANN) based on the Levenberg-Marquardt training algorithm of MATLAB software package was applied for prediction of the minimum temperature for the next 3, 6, 9 and 12 hours ahead. The selected Transfer Functions were hardlims, logsig, polsin, radbas, satlins, softmax, tansig, and tribas. The statistical measures of MAD, MSD, RMSD, and R were used for comparisons. The results showed that in case of late spring frost, the poslin, logsig, tansig, and satlin functions in April with a correlation coefficient greater than 0.8 and error values of 1.17, 1.61, 1.88 and 2.00 (◦C) for the different times steps, respectively are the best options. Similarly, in October, the radbas, poslin, poslin, and tribas functions with a correlation more than 0.7 and error values of 1.60, 1.96, 1.99, and 1.36, were found to be the most suitable ones for prediction of the minimum temperature at 21:30, 00:30, 03:30 and 06:30 local time. Also, among the selected functions, the poslin with the highest frequency has the best performance in predicting nocturnal frosts in Sanandaj. The results confirmed the good performance of the ANN approach in short-term prediction of minimum temperature and frost occurrence in study region.

Frost is one of the most important phenomena in climatology, which is caused by changes in temperature over time. The sudden occurrence of this phenomenon at the beginning and end of the cold period can be very dangerous for the agricultural sector. Therefore, the awareness of the frost time - occurrence has long been considered by researchers (Thom and Shaw, 1958; Rosenberg and Myers, 1962; Schmidlin, 1986; Watkins, 1991; Waylen, 1988). In order to manage the reduction of the effects of this destructive climate phenomenon on the agricultural sector and the exploitation of large regional environmental capabilities, it is necessary to notice seriously the detailed study of this phenomenon and its characteristics at the land level. And this will be costly and time-consuming. Therefore, with the purpose of preventing the last two factors and at the same time achieving managerial goals, it seems necessary to accurately zoning and recognizing homogeneity and non-homogeneity between different areas in a large area.  

In the first step, daily minimum temperature data were adjusted based on Julius day, and the averages of the five indicators including the day of the onset of frost, the day of the end of frost, the annual number of days of frost, the length of the frost season, and the length of the growing season were extracted. In the second step, the five indicators were modeled separately with three land-climate factors, namely altitude, longitude, and latitude of the stations, using multivariate regression models. To measure the accuracy of the obtained models, four basic assumptions were examined (). Using the regression models obtained for all parts of the province, the statistical indicators of the frosts were calculated and generalized to the points without stations. Finally, using the kiriging method, each of the five frost indicators of the province was zoned.  

The correlation coefficient of three variables, altitude, length, and latitude with different frost indices was obtained by simultaneously entering these three variables into the regression model. And four basic assumptions for measuring the accuracy of the obtained models were confirmed. The earliest occurrence of the first day of frost arises between September 21 and October 27, and in the mountains of northwestern Kurdistan, especially the Chehel Cheshmeh. The latest occurrence of the first day of frost also happens in the eastern lowlands of the province between October 17 and November 23. The earliest occurrence of the last day of frost arises between March 22 and 30 in the lowlands of southeastern and southwestern Kurdistan, and the latest happens between May 24 and June 1 in the high peaks of the west and northwest of the province, such as Chehel Cheshmeh Heights at an altitude of about 3173 meters, Ketresh Mountain with a height of 2592 meters, and Vazneh Mountain with a height of 2697 meters. The highest frequency of frost is in the mountains of the region with more than 196 days and the lowest frequency is in the eastern borders of the province with less than 72 days. The northwest mountains with 235 to 248 days and the eastern and southeastern regions of Kurdistan with 123 to 137 days, respectively, have the longest and shortest length of the frosted season. The longest growing season belongs to the eastern part of the province. The average growing season in this area is between 214 and 227 days. However, within this area, small sections that are lower in height have a longer growth period. On the other hand, the shortest growth period is in the western and northwestern mountains, averaging 116 to 129 days.  

The results show that the three factors of altitude, latitude, and longitude can determine between 72 and 95% of the changes in different frost indicators. These three factors explain the 95, 90, 88, 80, and 72 percent changes in the length of the growth period, the occurrence of the first day of frost, the length of the frosted period, the frequency of frost, and the last day of frost, respectively. The Coefficient of determination is 95% for the first day of frost and 72% for the last day of frost. It seems that other factors besides the three mentioned factors play a role in changing the date of the last day of frost. Therefore, based on the studies of Noohi et al. in 2007, Noohi et al. 2009, and Alijani et al. in 2014, it can be inferred that the end frosts of the cold period can be more than the type of the advection frost. In other words, the synoptic factors can play a more important role in the occurrence of the last days of frost and its variability. But the spatial arrangement of different frost indices in Kurdistan province indicates a western to the eastern arrangement in the values of different frost indices. This means that with more movement from west to east, the number of frost days as well as the length of the frosted period decreases, and as a result, the growing season increases. In accordance with these changes, the occurrence of the first day and the last day of frost also arose with many delays between the eastern and western parts of the province. A comparison of the maps obtained from this algorithm showed that this method can provide more accurate details of the frost indicators compared to the zoning that used only stationary data (Mianabadi et al., 2009 and Ziaee et al. 2006).

Climate classification systems(CCSs) are important tools for understanding the specific characteristics of a region's climate. The main purpose of these classifications is to determine the climate types and to find their similarities, differences and variability. Climate zones are threatened by global warming and climate change. The purpose of this study is to evaluate the possible shifts of climate zones over the Balochistan plateau of Pakistan and its potential challenges to Iran based on the improved Koppen-Geiger CCSs. The data includes average monthly precipitation and temperature of the Delaware university dataset for the 1990-2017 periods. The results show the main climate with two subgroups in the study area. These climates include a hot desert climate(BWh) and a cold desert climate(BWk). The hot desert climate is dominated in southern and western and the cold desert climate in northern and western regions.In recent decades, the increasing range of hot desert climate limited the cold desert climate. The range of the cold desert climate has declined sharply, reaching from about 55-65 to about 50-55 percent. In contrast, the range of hot desert climate increased in response to these conditions, reaching from about 35-45 to about 45-50 percent.Therefore, it is expected that the zones of the hot desert climate will increase rapidly in the future. These conditions will add to environmental quality and resource depletion problems especially in border areas with Iran and can pose important challenges such as climate migration, border security, and health. The results of this research can play a significant role in adopting forward-looking policies to address the impacts and challenges of climate change on the border regions of Iran.

Introduction :

The temperature in the troposphere usually decreases with increasing height, therefore, with increasing distance from the ground, the air temperature will be lower (roughly 0.6 degrees Celsius per 100 meters. However daily atmosphere evaluation shows unlike the above description, in many cases the opposite is seen to be called inversion. The purpose of this study was to investigate the adaptive trend of inversion of the temperature of the boundary layer of Tehran, Mashhad and Tabriz metropolis in 2007-2017 on the daily, monthly and annual time scale. 

Materials and methods:

 The atmospheric sounding data from the Meteorological stations of Tehran, Mashhad and Tabriz for the years 2007-2017 were extracted from the Wyoming climate database at 0 o'clock. In order to determine the types of temperature inversion in each metropolis, the graphs of the atmospheric data of each station were mapped using RAOB software and the total number of days with temperature inversion was extracted at the stations. Three types of radiation, superstructure and frontal inversion were identified as three main types and four other types as combinational types of these three types of inversion. Then the frequency distribution and percent of each of the seven inversion types were calculated for each station in the 12 months of the year. The eleven-year process of each inversion type was determined using the non-parametric Man-Kendall method and the estimator of the Estimator slope and compared with each other. 

Results and discussion:

 Results analysis indicated that from the seven inversion types, the inversion type of radiation in the three stations under study in all months of the year has been quite decreasing and significant trend at 95% and 99% levels. The subsurface inversion type at all three stations showed a positive and significant trend at 95% and 99% levels in the most months of the year. The trend of forward inversions in the stations under study has been decreasing for the most months (the Z score and Sen’s Estimator Slope is negative). Radiation-submerged-frontal combined type inversion in the study period in all studied stations in most months has no significant trend. Among the seven types of inversion observed at the studied stations, the combination of radiation-subsidence type has the most significant and incremental trend in all three stations. In all three stations, for 6 months of the year, the increasing frequency of radiation-subsidence type at 95% and 99% confidence levels was significant and the most frequent increase in this type of inversion occurred in the winter and autumn seasons. The combined type of radial-frontal inversion and the Subsidence- frontal type at all stations in Tehran, Mashhad and Tabriz have not been significantly trendy for most of the months. The investigation results of the number of inversion layers in the stations showed that in all three stations in all months of the year, the number of inversion layers increased significantly at 99% and 95% confidence levels. An annual review of the frequency of inversion days in all three stations showed a significant increase in the annual scale. In this study, using the inversion layer temperature difference, the thickness of the inversion layer and the station height were used to calculate the intensity of the inversions. Formula (1) I=((Δθ)2)/(3+Z(Δz)) The inversions were calculated only for inversions of the surface of the earth up to the surface of 500 hPa, then by applying the two conditions of the Haffter ((Δθ / (Δz)> 0/005 km ^ (-1) and θ_"t" -θ_"b" >2( Critical inversion was investigated by the total inversion occurred and the severity of the inversions trends. The results of applying the Mann-Kendall test and the Sen’s Estimator Slope on the data of the severity of critical inversions in different months of the year showed that except for the months of October, November and December at the Mehrabad station, the rate of critical invertebrates was significant at 95 % level. For the rest of the months, the trend of severity of critical inversions has been increasing, but they are not significant at all levels of confidence. In February, the trend of inversion was decreasing in all three stations. Conclusion The results showed that the radiation type inversion occurred in the period 2007-2017 at all three stations decreased significantly, conversely, the subsidence inversion type showed a significant increase in all three stations. Radiation- Subsidence combined type had a significant increase in all three stations. It can be concluded that the types of inversion in the period of 2007-2017 have changed from pure inversion types to combine and multi-layer types and, specifically, to the Radiation- Subsidence type. The significance of the increasing trend of inversion layers was also confirmed by statistical tests. Despite the increasing trend of the inversions occurring during the statistical period, this trend has not been significant at any level of confidence. However, the intensity of inversions other than the fall of Tehran station at other stations did not have a significant trend, although they have experienced a positive slope for many months. Several factors, including the release of high heat energy, the increase of greenhouse gases, as well as the increase in population and land use change, the change in surface evolution from heat transfer, pollutant emissions, evapotranspiration and land cover due to the impact of wind currents considered to be reasons of this increased air stability in the boundary layer and the local climate change of these metropolises.Despite the increasing trend of the inversions occurring during the statistical period, this trend has not been significant at any level of confidence. However, the intensity of inversions other than the fall of Tehran station at other stations did not have a significant trend, although they have experienced a positive slope for many months. Several factors, including the release of high heat energy, the increase of greenhouse gases, as well as the increase in population and land use change, the change in surface evolution from heat transfer, pollutant emissions, evapotranspiration and land cover due to the impact of wind currents considered to be reasons of this increased air stability in the boundary layer and the local climate change of these metropolises.

 With recent advances in satellite remote sensing productions in past few decades, several indices have been provided for the study of vegetation dynamics, and especially for the assessment of drought impacts. Among these, two vegetation indices -Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) - have gained the attention of various researchers. Therefore, the present study aims to investigate the reaction of these two vegetation indices (i.e. NDVI and EVI) to dry and wet years in a dry plain in Iran (i.e. Sistan plain in eastern Iran).

To assess the sensitivity of these indices to dry and wet years, two different databases were required. First, NDVI and EVI image base received from Terra satellite (MODIS sensor) for April, May and June 2000-2014, and downloaded from EOS website. Second, daily data base of Zabol synoptic meteorological station (for a statistical period of 30-years 1985-2014) received from Iran Meteorological Organization. After data acquisition, separate vegetation dynamics maps (for April, May and June) were produced for the study area based on the information derived through processing of MODIS sensor images (Terra satellite) using NDVI and EVI. Effective drought index (EDI) was used to determine the frequency of dry and wet years in Sistan plain.

Mapping of vegetation dynamics based on images received from MODIS sensor (Terra satellite) for a 15-year statistical period (2000 to 2014: April, May, and June) indicated that NDVI and EVI had significant differences in exhibiting the dynamics of vegetation in the study area. These differences were obvious in areas with average amount of vegetation (0.4-0.5 in both NDVI and EVI) and also in areas with sparse dispersed vegetation (0.3-0.4 in both NDVI and EVI). In average levels of vegetation, total area of vegetation calculated by EVI is​​ much higher than what is calculated by NDVI, while in sparse and dispersed vegetation, total area of vegetation calculated by NDVI is almost higher than EVI. Subsequently by selection of a dry (2010-2011) and a wet year (2005-2006), we compared changes in total area of vegetation (average and sparse) calculated by NDVI and EVI. Regarding the response of these two indices to dry and wet years, it was concluded that NDVI shows a better and more logical response during droughts, while EVI provides better results in wet years. However, it should be noted that the mean annual precipitation of Sistan plain is so low (59 mm per year) and its evapotranspiration is so high (4800 mm per year) that precipitation does not play a significant role in vegetation dynamics of this plain. Therefore, water flow in Helmand River, which is the lifeblood of this desert, is much more important than this limited precipitation in Sistan plain; hence, we can conclude that meteorological drought monitoring indices cannot reflect the relationship between drought and vegetation dynamics in Sistan plain, and this makes it difficult to compare NDVI and EVI in the region.

In general, it can be concluded that NDVI is a more suitable index for dynamics of vegetation in plains such as Sistan, whose life depends not on precipitation but on water running in the river. Because of the computational nature of EVI, it responds better in areas with dense vegetation. According to the vegetation type obtained from MODIS sensor images and field visits, NDVI is a better index for these types of plains.

The purpose of research is to rezoning the climate zones of the north east of Iran- located between 30° 35' to 38° 41'N and 56° 19' to 61° 16'E- based on the analysis of changes in the aridity index, in combination with other climatic parameters changes. Air temperature and precipitation parameters were provided in the scale of monthly average and annual over period time of 1990-2017. At first, the climate classification of the north east of Iran was revised by studying variations in precipitation, evapotranspiration and temperature and results were compared with the De Martonne and Köppen-Geiger climate classification. For analyzing the aridity status, trend of the above parameters in the form of UNEP index was tested using Mann-Kendall non-parametric method and Sen's slope estimator. Results indicated that applying of the aridity index, as a factor in improvement of the used pattern, caused the zoning of this method to be more precise than the previous methods. Therefore, the study area was classified into seven climatic groups, the zone Ac14 (Arid zone with cold winter and hot summer) with 39% and 9 stations, and Ec14 (Extremely-arid zone with cold winter and hot summer) with one station were the largest and smallest climate zones, respectively. Results of the Mann-Kendall test and trend line slope, for UNEP aridity index showed that the aridity and desertification intensity have increased in different parts of the area during 28 years.

The aim of the present study is to examine the relationship between urban floods and structural and environmental factors in Zahedan City. Zahedan City located in small and plane surrounded by low-height Mountains. Historical reports have recorded big and destructive floods with long returning intervals for this cityStructural factors examined in this research for localization were: topography, slope, land use, and watercourse any of which were covered and weighted by AHP method in form of a plan and as a factor by GIS software. Determining the privilege of factors was conducted by questionnaire and Delphi method and factors were compared two by two by expert choice and the level of inadaptability reached to 0.1. After overlapping, flood zoning map in Zahedan was provided. The results of final localization map of dangers for flood show that around 17 % of urban lands in Zahedan are in a large danger, 42% in relative danger, 28% in normal status and 12% in status without danger. Thus, given the effective role of structural, environmental, and climate factors in creating watercourse and flooding potential, the most vulnerable parts in Zahedan City were identified. These districts include the ending parts of Moradgholi and Razmjomoghadam streets and the beginning part of Imam Khomeini, Saadi and large parts of Shahid Rajaeii streets.

One of the most important incidents of heavy precipitation is that each year there are many damages. Precipitation regimes help to identify the climate of each region. A heavy precipitation regime can help in identifying the climate of each region. Identification of these regimes is one of the most important prerequisites for environmental planning, especially water resources management and land management Programs.In this research, Iran's heavy precipitation regime is planned for the period of 20 years (1996-2016). In this study, for the implementation of the PCA model, a 153 ×12 matrix was created. Then, from the types of rotations in the factor analysis, the Equamax period had the most appropriate load factor on the study stations. Therefore, the analysis showed that 6 factors explained about 89% of cumulative dispersion. The 8 regions of the diagnosis include: Caspian Sea (Caspian coastline), North Azarbaijan (Iranian and Azerbaijani border stations), Azerbaijani regime (stations from central and southern Azerbaijan), Southern Zagros regiment (Khuzestan plain and coastal strip and Persian Gulf shelters)., Mountainous region (mountains of western Iran and mountainous regions surrounding and dispersed in Khorasan), the Dry Central - East - South Coast regime (a large part of Iran), the Eastern Alborz regime (regions of northwest of Iran and stations of Golestan province), the middle Zagros regime The western part of Iran and dispersed in stations from northwest of Iran).

The radative energy balance received and returned from Earth planet reflects the energy available in each part of the Earth-Atmosphere system. Also, net solar radiation is the most fundamental driving force for evaporation, and all actions and reactions between the Earth's surface and the atmosphere. These reactions significantly affect the climate and its transformations. Hence, the wide-scale cross-sectional estimation of pure net energy is important in terms of global and regional climate models. In this research, in order to study the trend of long-term monthly average changes of surface-Albedo, the Albedo products from the sensors of MODIS Satellite Terra named MCD34B4were used. The spatial resolution of the images taken was 1×1 km for a 11-year statistical period (2222-2213) for April, May, and June. After capturing images by NASA's land processes distributed active archive center, all 31 downloaded images. The next step was to convert the image format to ASCII format; each ASCII includes 42202 pixels. Finally, by using both statistical methods of Sen's slope estimator, and Classic Linear Regression the trends of long-term monthly average Albedo changes were analyzed on a pixel-based scale. The results of these two models showed that these two models did not differ in their estimation of the trends of Albedo's average changes, and acted precisely the same. Also, the results of this research showed that the center of the most slowly declining slope of Albedo changes is located in the northeast, where, due to the flow of the Hirmand River, in this part of the plain the agriculture is widespread. The incremental magnitude of the slope of the change process is also very limited, and there are small and large spots in the north, northeast, and center of the plain. This increasing trend in the values of Albedo's index in the north of the plain was exactly the same as the drying of the Hamoon triple lakes. The rest of the plain area, which has desert landscape and does not have any vegetation, as well as any human population, has not shown any particular trend. In this study, it was also clearly found that, the use of nonparametric method of Sen's slope estimator and parametric method of classic linear regression can be very effective in studying the trend of Albedo changes in the arid regions resulted from satellite products of MADIS sensors.

Green spaces in the urban environment can contribute to reduce the Urban Heat Island. In a context of climate change, with the expected increase in temperature, dryness and intensity of heat waves, green areas assume even higher importance as they can create a cooling effect that extends to the surrounding areas. This study analyses the thermal performance of Golmohamady Park (9.2866 ha) with vegetation cover (7.5464 ha) and its influence in the surrounding atmospheric environment space in Esfahan. Measurements of weather parameters (temperature, relative humidity and wind speed) were carried out along a selected path, starting from inside the green area to surrounding streets with different orientations and solar exposure. It was found that the park was cooler than the surrounding areas, either in the sun or in the shade. These differences were higher in hotter days and particularly related to the mean radiant temperature (Tmrt). The highest difference found was of 6.7 C in relation to air temperature. In both cases this difference occurred between the shaded site inside the park and the sunny site in an E-W oriented street in the North of Golmohamady Park. Besides the local weather conditions, particularly the low wind speed, the sun exposure and the urban geometry are the potential factors that explain these differences. The cooling effect of green spaces on the surrounding environment can be enhanced by additional measures related to the urban features of each city.

As 7 Stations include; Ardebil, Sarab, Shahrekord, Ahar, Takab, Zanjan, and Saghez were experiments on average every year less than 30 days with thermal stress. From these 7 stations, Ardebil and Sarab regions, having 3 and 7 days with thermal stress, respectively, have the least amount of days with heat stress. All the days with the heat stresses obtained for these stations have been the days of the first class of heat stress map, and all of them were randomly distributed over the warm period of the year.
But in contrast to this stations that had the fewest days of thermal stress, southern Iranian stations, especially those stationed at the Persian Gulf and the Gulf of Oman Sea coasts, were the most frequent days of heat stress.
The two Jask and Chabahar stations with the annual average of 304 and 301 days, with the highest thermal stress, were the most frequent regions of Iran. The lower latitudes, lower elevation, higher temperatures and relative humidity are factors that make the conditions for having the most frequencies of days with heat stress in this part of Iran.
The spatial pattern of five classes this index also show different patterns in comparison with each other so that as all stations in Iran experience at least 3 days of thermal stress in the first class during the year. But with increasing intensity classes, the number of stations that experience the conditions of these five classes over a year will be reduced. As for the second class, 16.2% of the stations, for the third class, 55.4% for the fourth class, 83.7 %, and finally for the fifth class, 90.5% of stations, do not experience comfort in any way during one year. Finally, with regard to the important role of the elevations in the spatial distribution, the relationship between the total frequency of days with thermal stress and elevation was modeled using classical linear regression model. The results of this model showed that per 100 meters above sea level, 9 days from the total frequency of days associated with Iran's thermal stress is reduced. This downward trend is such that there is no thermal stress in Iran at 2300 m above sea level. In other words, the height of 2300 meters is the elevation border between the occurrence and absence of days with thermal stress in Iran.

Climatic variables are considered as one of the most important factors affecting the spatial-temporal dynamic of vegetation. Nowadays, satellite images are widely used for monitoring the effect of climatic variables fluctuations on vegetation changes. The purpose of this study is to investigate the relationship between two climatic variables of precipitation and temperature with vegetation dynamic in one of the world’s dry plains i.e. Sistan plain in eastern Iran by using satellite data. In the present study, the data generated in NDVI related to MODIS sensor of Terra satellite for 3 months of April, May, and June over 2000 to 2014, data of temperature and monthly precipitation (October- September) in Zabol meteorological station were used for the same time period of 2000-2014. Pearson product moment correlation was used to study the relationship between climatic variables with NDVI. The results showed no correlation between MODIS NDVI of April, May, and June with the average temperature of previous months in terms of monthly scale. In case of precipitation, it was observed that the precipitation of May with MODIS NDVI of May 0.603 and June 0.542 had a normal positive correlation. But due to the very low amount of precipitation and high evaporation in this month, this correlation cannot be trusted a lot. Thus, by recognizing no correlation between climatic variables and vegetation dynamic in Sistan plain, the correlation between the average annual discharges of Hirmand River was considered as the only river in this plain with MODIS NDVI of April, May, and June. The results of correlation showed a strong positive correlation of 0.75 between the average annual discharges of Hirmand river and MODIS NDVI of April. Thus, it is obvious that the critical vein of Sistan plain is Hirmand river and the life in this land and its vegetation dynamic depends not only on temperature fluctuations and precipitation but also on the water of this life-giving river.