جستجوی مقالات مرتبط با کلیدواژه « پارامترهای اقلیمی » در نشریات گروه « جغرافیا »

Soil and air are two essential elements in the life of creatures on the earth. Their interaction in certain conditions can cause many risks; among these dangers, dust storms can be mentioned. Under the conditions of dust storms, a large amount of dust is emitted in the air and the horizontal visibility is reduced to less than 1000 meters. Therefore, due to the important role of the dust phenomenon, it is highly necessary to understand the spatial-temporal changes and to analyze their long-term variations. Jazmurian region, located in the southeast of Iran, between the two provinces of Kerman and Sistan and Baluchistan, has become completely dry and turned into a desert due to drought and construction of numerous dams, and has turned this region into one of the key areas of dust production in the country. Therefore, the purpose of this study is to investigate the temporal-spatial changes of dust storms in relation to climatic parameters in Jazmurian wetland, which is of particular importance in order to properly manage this area to face the problems caused by dust storms.

In order to carry out the present research, the meteorological data related to the synoptic stations located in the Jazmurian wetland area for a period of 20 years (2000-2020) were received from the Iranian Meteorological Organization. Climatic data used in this research include temperature, precipitation, relative humidity, wind speed and direction, horizontal visibility, and remote sensing data including Aerosol Optical Depth (AOD) and Normalized Difference Vegetation Index (NDVI). The research method uses a combination of statistical analysis, observation and remote sensing. In order to check the AOD and NDVI, the monthly data of MODIS sensor was used. In this study, 12 synoptic stations that had the longest and most complete statistical periods were used in order to identify the temporal-spatial changes of dust occurrence in Jazmurian wetlat. The Mann-Kendall test was used to examine the trend of time changes. The slope of the Sen estimator was used to check and confirm the accuracy of the trend changes. In order to better understand the spatial distribution pattern of dust events in the Jazmurian wetland basin, the inverse distance interpolation method (IDW) was used. Also, Pearson's spatial correlation analysis was used to investigate the mutual effects between the indicators.

The 20-year average review of the indicators showed that the maximum value of aerosol optical depth in the studied area was 0.3, which is seen in the central part of the wetland. The vegetation index also showed that the maximum value of this index was 0.2, which covers most of the northern, northwestern and western parts. Examining the average rainfall trend showed that the maximum and minimum rainfall in this period are about 219 and 85 mm, respectively. Meanwhile, the 20-year average temperature survey showed that the maximum and minimum temperatures were 28.7 and 17.2 degrees Celsius, respectively. The fact that the maximum rainfall is in the northern and western part is in harmony with the minimum temperatures in these areas. The examination of the average wind speed showed that the maximum speed was 3.6 m/s, which was mostly in the central, west and northwest, south and southwest parts. The results of the wind direction index showed that the lowest wind direction is in the northern parts of the region and the highest wind direction is in other parts of the Jazmurian wetland basin. The maximum humidity in the studied area is 43.73%, which is mostly seen in the north, northwest, west, south, and southwest parts.  Examination of the horizontal visibility index showed that the maximum amount of horizontal visibility was in the northeastern and northwestern parts of the region. Also, the process of changes in the Mann-Kendall test showed that the annual averages of the indicators of wind direction, wind speed and horizontal visibility have been increasing with a positive slope, and the trend of changes in the relative humidity index has a negative slope and indicates a decrease in the period of 20 years. The results of the correlation analysis (at a significance level of 5%) showed that the highest correlation of the optical depth index was with the wind direction parameter and the lowest correlation was with the relative humidity index.

The growing trend of the emission of dust particles caused by the phenomenon of wind erosion in recent decades has caused major concerns at different regional, national and global levels. Therefore, it is necessary to understand the temporal-spatial changes of the dust caused by these events in order to reduce their adverse consequences in different regions. Accordingly, in this research, with the help of this knowledge, information related to the optical depth of particles in the air (AOD) and the vegetation cover index (NDVI) were investigated using the MODIS sensor satellite data. Using the meteorological data received from the website of the National Meteorological Organization, the climatic data of rainfall, temperature, relative humidity, horizontal visibility, wind direction and wind speed were evaluated in the period of 2000-2020 and finally the correlation between the AOD index and other climate parameters was evaluated. The results of the optical depth investigation showed that the maximum optical depth is located in the central parts of Jazmurian wetland. The trend of changes in rainfall and temperature indicators also showed that the trend of these two parameters was increasing; this increase in temperature is more noticeable. Correlation investigation between optical depth and other parameters showed that the highest correlation of optical depth index was with the wind direction parameter and the lowest correlation was with the relative humidity index. In general, we can conclude that the optical depth of airborne particles is highly dependent on environmental factors, which is more evident in arid and semi-arid areas, especially in Iran and the Jazmurian wetland area. In recent years, the area of the wetland has acted as a source of dust. Therefore, by using the remote sensing data obtained from the MODIS sensor and the climate data, it is possible to examine and analyze the trend of dust changes in the units of time and space.

The present study aims to investigate the temporal-spatial trend of horizontal visibility in the southern coasts of the Caspian Sea. For this purpose, horizontal visibility and climatic parameters (relative humidity, temperature, precipitation, and wind speed) were obtained in 13 selected meteorological stations from 1951-2010. After the data screening, the temporal changes of the perspective were examined. Also, Ridit tests were applied to examine the trend of horizontal visibility, and a correlation coefficient was used to identify the relationship between the climatic parameters effective in reducing horizontal visibility. The results of the research showed that the average annual dispersion of horizontal visibility in the studied stations experienced relatively different periods; the first period from 1951 to 1976 period of horizontal increase, the second period from 1977 to 1985 period of noticeable decline, the third period from 1986 to 2002 fixed period (no fundamental change) and the fourth period from 2003 to 2020 relative increase. Among the stations, the highest negative correlation coefficient was experienced by Astara station, with a value of -0.47, and the lowest was experienced by Sari station, with a value of -0.07. In the correlation between horizontal visibility and precipitation in the studied stations, the maximum significant negative correlation was observed in the Manjil station (with a value of -0.15) and the least in the Maratape station (with a value of -0.012). The correlation between horizontal visibility and temperature is direct and positive in most stations, and the maximum positive correlation is assigned to the Astara station with a value of 0.38. It also showed a negative correlation between wind speed and horizontal visibility. The inverse correlation's maximum and minimum range fluctuates between -0.28 in Sari and -0.08 in Babolsar.

Over the past hundred years, human activity has significantly altered the atmosphere and increase of concentration of greenhouse gases lead to warm the earth's surface. This global warming leads to change of climatic extreme index and increases the intensity and frequency of occurrence of extreme climate events. Investigation of extreme values for planning and policy for the agricultural sector and water resource management is important.In this study, a comprehensive review of extreme indices of temperature and precipitation are discussed. This paper aims to investigate extreme temperature and precipitation indices defined in accordance with CCL, and the study of other climatic parameters in Iran.

In this research, statistics and data of 27 stations in the Iran during the period 1958-2017 were used. To evaluate the extreme climate indices trend, 27 indices of rainfall and temperature, were defined by the ETCCDMI. They were calculated by RClimdex software. In this software, prior to the index calculation, data by quality control software became quantitative and incorrect data were controlled and outlier data were examined. The indices were calculated by daily data. 11 rainfall and 16 temperature indices were calculated by this software.The target of the ETCCDMI process is to delineate a standardized set of indices allowing for comparison across regions. These extreme indices were classified in five categories which included the percentile-based extreme indices, the absolute extreme indices, the threshold extreme indices, the periodic extreme indices, and the other indices. They were estimated at the 0.05 significant levels. The Mann-Kendall test was used to investigate the climatic parameters, temperature and precipitation.

Thermal analysis results are consistent with warming patterns, and they have showed that hot extremes indices have increased. Hot days index (SU25), shows a significant positive trend in all studied stations. Number of tropical nights has a positive trend in all stations. Hot day frequency (TX90P) and hot night frequency (TN90P) in most of stations show a positive trend, indicating an increase in the number of warm days and nights. Cold extreme indices show a decreasing trend. (TX10P) and (TN10P) show significant negative trends in all stations and indicate a decrease in cold days and nights. Number of frost day index shows a decreasing trend. Overall, the results revealed a decrease in the severity and frequency of cold events, while warm events during the study period were significantly increased. Comparison of years with the highest rainfall and those with the lowest, showed that the amplitude of fluctuations in precipitation in different years is very high and the distribution of rainfall at distinct stations is different.

The results showed that intense warm indices, such as the summer day index, the number of tropical regions Warm nights, days, and nights have increased, while during the study period, severe cold indices have decreased. Trends, which show a decrease in the intensity and frequency of cold events. the door There was no significant trend in rainfall indices during the study period.

Today we are faced with contexts that due to lack of living facilities, lack of meeting the needs and wants of the people Most of their natives have migrated, and generally the lower classes and outsiders have settled there simply because of their financial inability. Who are devoid of a sense of belonging to the place and its identity and regardless of the values hidden in it; Which have degraded the fabric of all social, physical and economic values Sustainable urban regeneration approach as an optimal approach with comprehensive and integrated vision and practice that tends to improve various dimensions of sustainability including economic, social, physical and environmental sustainability The aim of this study is to identify and explain the most important factors and strategies affecting the sustainable regeneration of worn and inefficient tissue of Ansar and Arvand neighborhoods. The research method is descriptiveanalytical with an applied purpose. In the qualitative part, the information collected through interviews with experts is analyzed in accordance with the information obtained from library studies and theoretical research literature by thematic analysis. Analysis and in quantitative part, in order to analyze the data collected from the questionnaire and semi-structured interviews and also to evaluate the impact and importance of the indicators extracted from the theoretical foundations in realizing the regenerative approach of the structural-interpretive model and to prioritize the indicators from The TOPSIS technique is used . According to the results, the strategies of "simplification and transparency of regulations and stages of issuing construction permits", "anticipating the necessary measures in the plans and plans of rehabilitation, improvement and renovation to satisfy and temporary housing of residents of areas and neighborhoods that are demolished and rebuilt Neighboring buildings are necessary in them and deprive their residents of the possibility of living And "creating appropriate institutional and legal contexts for the management of the target neighborhoods" is at the lowest level and is one of the most important strategies in the realization of regeneration in Ansar and Arvand neighborhoods.

Air pollution, especially in the two pollutants of suspended particles less than 2.5 microns and sulfur dioxide, is one of the important problems of large and industrial cities of Iran, including in Tehran, especially in the cold half of the year, which affects the health and comfort of citizens.

The severity and weakness of air pollution in Tehran is related to climatic patterns and the dominance of air masses over the city of Tehran.

By following the air pollution during the year 2019, this research investigated the pollutant variables on a monthly, daily and hourly basis for 4 districts 2, 5, 9 and 18 of Tehran city in five pollution measurement stations and based on three climate scenarios: effect of stability, instability and inversion, separate clean and polluted days and investigate the role of air masses dominating the city for both conditions. To better understand the relationship between the weather patterns governing the study area, atmospheric conditions at 1000 and 500 millibar levels, as well as the earth's surface map, have been analyzed. Air pressure, temperature, rain and wind are the elements that have been investigated. Pollutant measurement data were obtained from stations located in the four districts of Tehran municipality and from the air quality control company affiliated to Tehran municipality, and meteorological data were obtained from the country's meteorological organization, and finally, radiosonde data from Mehrabad station were used for the inversion study.
Geographical Context: the area of study in this research is Tehran and its 4 municipal zones 2, 5, 9 and 18.

The research results show that the air quality of the study area has a strong dependence on the development of the geopotential ridge in the middle troposphere, the absence of wind blowing at a significant speed on the surface of the earth, the extreme stability of the air and the creation of a dynamic inversion layer or subsidence at high altitude. In other words, periods of air pollution intensity are related to weak pressure gradient, calm wind, air subsidence and temperature inversion.

Finally, during severe and critical pollution, high-pressure air dominates the city surface and the air is stable, and the wind either does not exist or is less than 3 meters per second, which does not have the power to purify the air. In the defined scenarios, the presence of strong wind (over 6 meters per second) is the best solution for having clean air, and rainfall is effective in removing pollution only when it rains heavily and for a long time.

Tropospheric aerosol particles play an important role in the Earth's radiative energy balance directly by scattering and absorbing solar radiation and indirectly by modulating the microphysical and radiative properties of clouds. Aerosol optical depth (AOD) based on satellite remote sensing data is a quantitative estimate of the amount of aerosol in the atmosphere and can be used as an indicator of aerosol particle concentration. In general, the review of previous studies indicates the high importance of aerosol products based on satellite remote sensing data in modeling the spatial-temporal patterns of dust storms and in particular the identification of dust sources. The advantages of using satellite AOD to identifying dust events are possible in arid areas with relatively little cloud cover. The presence of clouds in the sky also severely limits AOD terrestrial and satellite measurements. Thus, AOD datasets sometimes have a gap due to factors such as cloudiness. Since the possibility of monitoring and measuring aerosols in cloudy conditions is limited, the use of proxy datasets to fill the gap will be an advantage. In this regard, several studies based on the analysis of satellite data have emphasized the association between climatic parameters and dust events (specifically AOD) in different regions. Therefore, considering the relationship between climatic parameters and AOD, these parameters can be used as a proxy data set to estimate AOD values for areas without data or with cloud cover. Also, using the predicted values of climatic parameters, AOD values can be predicted. Accordingly, in order to achieve reliable AOD prediction results, it is necessary to use a generalizable approach that can model the complex relationships between large data sets and satisfactorily solve the mentioned problems. For this purpose, one of the efficient data mining algorithms called M5P was considered to analyze and extract the relationships between climatic parameters and AOD to obtain predictive models. The M5P algorithm is a combination of tree and regression models with capabilities such as high prediction accuracy and ease of interpreting results.

In this study, in order to derive AOD predictive models based on climatic parameters, M5P data mining algorithm based on tree structure and multivariate linear regression analysis were used. Accordingly, a spatial database of remote sensing time series data related to 4 climatic parameters (as independent variables) including surface air temperature (SAT), precipitation (P), surface relative humidity (SRH) and wind speed (WS), and AOD (as dependent variable) was generated. WEKA software was used to implement the M5P model. After analyzing the relationships between independent and dependent variables through the tree model structure and linear multivariate regression, AOD predictive rules were extracted. Statistical indicators were used to validate the linear predictive models.

After pre-processing the time series data of climatic parameters and AOD as training data set, the input independent and dependent variables of the M5P were defined. Implementation steps of the M5P algorithm, including homogenization of independent input data sets by forming decision-making trees based on a series of "if-then" rules, multivariate linear regression analysis in homogeneous classes, and finally validation of the model results was performed in WEKA software. Thus, a total of four linear models (LM) or predictive rules for estimating AOD based on the values of climatic parameters were extracted. Finally, by placing the values of climatic parameters in the obtained linear models, the AOD value can be estimated based on the thresholds defined by the M5P algorithm. The obtained linear models are able to predict AOD values in different conditions (based on climatic parameters). Validation of the results of the M5P algorithm based on correlation analysis between input variables and evaluation of prediction errors through MAE and RMSE statistics shows the acceptable performance and accuracy of linear models in relation to AOD prediction. Given the dynamics of aerosol particles (especially dust) and their ability to transportability by the wind even at very far distances from their source of emission, it is likely that the amount of measured AOD for a pixel by a satellite sensor, does not exactly belong to the same area on earth. Therefore, in relation to the prediction error of the models, it should be noted that this may be due to the ability of the aerosol particles to be carried by the wind. Due to the strong correlation between AOD and climatic parameters, possible discrepancies may be due to the mentioned reason. Because a dust storm arising from a source may have no relation with the values of the climatic parameters at the destination.

In general, in this study, the capability of M5P data mining algorithm in order to AOD prediction was evaluated. Using the M5P algorithm based on inductive learning and using remote sensing time series data, through the formation of decision trees based on the set of "if-then" rules, four linear predictive models based on climatic parameters were extracted. Predictive models were extracted and validated using a data set for Ahvaz city. AOD, as an indicator of the state of the atmospheric aerosol, has great importance for dust storms studies.Access to AOD data is restricted in some parts of the world and in some seasons due to some limitations such as cloud cover. On the other hand, it is important to be aware of future spatial-temporal patterns of dust storms in order to adopt crisis management measures. Using the obtained predictor linear models in this study, it is possible to make an acceptable estimation of AOD in some areas, there are restrictions on access to AOD. Also, by entering the predicted values of climatic parameters, it is possible to estimate the future spatial-temporal patterns of AOD.Dust storms generally occur as a function of a wide range of environmental conditions, including atmospheric properties, as well as surface parameters such as vegetation, soil moisture, and soil texture. With this background, only considering the atmospheric conditions and their impacts on the spatial-temporal patterns of AOD may sometimes not produce the desired results. Therefore, it is recommended in future studies in this field, in addition to climatic parameters, which are mostly indicators of the atmospheric condition; ground surface parameters should also be used in modeling. By doing so expected to increase the accuracy of linear models for predicting AOD.

Climate change and global warming are some of the issues and concerns of human beings today that have important effects on rain, evaporation, runoff, and finally water supply and causes the severity and weakness of these parameters, increasing the occurrence of severe weather events and lack of available water, which causes irreparable damage. Evapotranspiration is an important component in the hydrological cycle that is affected by various factors such as air temperature, relative humidity, wind speed and number of sunshine hours, and these factors are also affected by climate change. Due to the occurrence of climate change in the country in recent decades, it is important to study the changes in the trend of climatic parameters and their role in evapotranspiration in order to apply management methods to reduce evaporation in water resources. The Mann-Kendall trend test is an often-used method to examine changes in the data time series, but this test only expresses changes in the center of the data series, so Quantile and Bayesian multiple regression methods are used to study the trend of changes in different parts of the data time series and also to investigate the role of various parameters on a specific parameter. Therefore, the purpose of the present research is to study and compare the trend of changes in evaporation and climatic parameters affecting it and determining the role of these factors on evaporation using Quantile and Bayesian multiple regression methods at Hashemabad Gorgan station located in Golestan province.

In the first step, the meteorological data time series of evaporation, and the factors affecting it including average temperature, relative humidity, sunshine hour and wind speed were prepared for Hashemabad Gorgan synoptic station with a statistical period of more than 30 years (1984-2018) and the seasonal data series of these data were formed. The non-parametric Mann-Kendall test was performed to investigate the trend of changes in evapotranspiration and the factors affecting it and then Quantile and Bayesian regression was used to investigate the changes in various quantiles of data series and also to determine the role of changes in different values of each of these meteorological factors on evaporation.

investigation of the trend in the evaporation data series and the factors affecting it based on the Man-Kendall test shows that the aforementioned trend test shows a decreasing trend in evaporation only for winter, while the lowest changes in trend in different quantiles are in this season, and in Summer the increasing trend in evaporation has the highest slope in the range of 0.66-1.14% for lower and upper quantiles, respectively. In spring, the increasing slope of 0.75 in the upper quantiles gradually changes to a decreasing slope of -0.72. In autumn, the lower quantiles have a higher slope up to -0.66 and in winter, the quantiles have the lowest slope between -0.14 to -0.08. The results of investigating the factors affecting evaporation also show that changes in temperature have a greater share in the changes of daily evaporation and the bigger the quantile, the increasing slope increases. The relationship between relative humidity and evaporation follows a decreasing slope and ranks second after temperature. Finally, it can be concluded that in Hashemabad station of Gorgan, the Mann-Kendall trend test could not detect significant changes that have occurred in the process of the evaporation trend, but these changes have been revealed the best by the Quantile regression method. In summer, which is the driest and hottest season of the year, the trend of increase in evaporation is more intense, and due to summer cultivation in this region, water consumption in agriculture has increased in recent years and with this trend will increase further in the future.

Given the fact that climate change may not have occurred only in the average value of a data series, but extreme events might have occurred in some parts of the series so it is necessary to study different parts of the data series using methods such as Quantile and Bayesian multiple regression and the results of this research emphasizes this matter. Also, due to the necessity of studying evapotranspiration in the application of management methods for water resources, useful and practical results can be brought out by studying the changes in different ranges of evapotranspiration, especially it’s extreme and high values as well as the effects of changes in different ranges of climatic parameters on evaporation.

In addition to domestic dust sources, Ahvaz city is affected by most of the foreign sources of dust which is mainly due to locating in the passage of southeast-northwest winds and vice versa. In this study, internal and external dusts were separated to determine the role of climatic factors in the occurrence of dust in Ahvaz. Therefore, the data related to parameters and climatic phenomena affecting the occurrence of dust have been used. Besides, the analysis and comparison of different neural networks have been applied to figure out the importance of each climatic factor in the occurrence of dust. In this study, 70% of the data are entered the network as educational data and 30% as test data. The square sum of educational data error and test data, the relative error of educational data test data and also the correlation coefficient between the measured and estimated values have been compared to evaluate the accuracy of different functions. Finally, the model showing the lowest error rate and the highest correlation coefficient has been selected as the optimal model to investigate the contribution of climatic factors affecting the occurrence of internal and external dust. The results show that wind factor with a speed of more than 6 meters per second and then the wind less than 6 meters per second have played the most important role in the occurrence of internal dust. Moreover, rainfall-changes factor is the third effective one. In the case of foreign dust, since Ahvaz is influenced by the conditions of more remote areas that are almost outside the political borders of Iran, drought factors, SPEI and DTR indices, are considered as the important factors in the occurrence of regional widespread dusts that reach Ahvaz.

 saffron , which is one of the most valuable plant , needs a peculiar condition to grow up. Nevertheless, over 90 percent of the cultivation of this plant is in Iran based on the local method. By the survey of the effect of the meteorological parameters on the function of saffron and appoint the auspicious region to its cultivation. Based on these factors it can be helpful in the development of agricultural and economical condition of the cultivation , so the current paper tries to evaluate the most important meteorological parameters which have the main effect on the growth saffron for the last 27 years from the five synoptic statians by the comparison the solarr and AD years then recollected these data , and analyzed them by using gis .arc info and ABC softwares . at the end ,by the compilation of these data the final map , which is shown that 65 percent of the studied region are suitable to cultivate saffron in it was achieved . These area consist of the west and center part of the province and the southeast is the week place to cultivation.

Airborne dust is an important environmental hazard in arid and semi-arid regions. Dust deposition rate is one of the most important characteristics of airborne dust which needs to be measured for risk assessment and source determination. During the past decade, by increasing the dust deposition in Iran, many investigations have been conducted to document the dust deposition characteristics and identify the regional atmospheric and land surface processes controlling dust transport. The objective of this study is to measure the dust deposition rate and investigate the effect of climatological factors on airborne dust in Khorasan Razavi Province located in the northeast of Iran. Khorasan Razavi Province is located in the northeast of Iran. Elevations range from 235 m in Sarakhs in east to 3211 m at Binaloud Mountain in north of the area. Mean annual precipitation varies from 111.5 to 306.3 mm and the mean annual temperature is between 12.7°C to 18.9°C. The Kopeh Dagh and Binaloud Mountains are in the northern part of the area. There are several playas (including clay flats, salt crusts, and sand dunes) in the south and western of the Province. Airborne dust samples were collected monthly from May 2014 to April 2015. A dry flat collection tray with an area of 1 m2 was used to sample airborne dust. Fifty trays were placed on the roof of buildings ~3- 4 m above the ground level. Dust trapped on the trays were collected by a rubber spatula and then were weighted. Totally, 600 samples were collected from 50 sites in the Province. Interpolation in this study was carried out using surfer software 14. Furthermore, the Grads software was used to draw the average monthly wind speed, direction patterns, and synoptic pattern of dusty days. The Pearson coefficient was used to determine the correlation between the characteristics with normal distribution. The measured dust deposition rate indicated the significant spatial and temporal variations during the studied period. The lowest and highest average monthly dust deposition was 9.97 and 20.96 g m-2 which occurred in December and June, respectively. The annual dust deposition rate showed high variations from 313.14 g m-2 y-1 in Gonabad with desert climate regime in southern to 74.62 g m-2 y-1 in the city of Quchan with temperate-mountainous climate in northern part of the area. In spring and summer, the dust deposition rate was the highest in the west and the south of the Province and also indicated the high range of variations. In autumn and winter, the range of dust deposition rate decreased and also the highest amount of deposition occurred in the east. The lowest amount of deposition was found in the mountainous northern part of the area. There was a significant positive correlation between the average dust fallout and the mean wind velocity and the maximum and minimum monthly air temperatures, while there is a significant negative correlation between this parameter and relative humidity. The spatial distribution analyses showed the highest amount of dust fallout in the southern and western parts of the Province, which includes the desert and sub-desert climate and also the most storm occurrences in spring. Also, in the months with higher rainfall, the amount of fallout rates decreased in most areas except the east of the Province. The high speed of wind, the dryness of the soil and the high occurrence of dust storm in June and July have caused the dust to be carried a long distance as compared with other months. The results of this study indicated the hazard of dust deposition rate, especially in the south and west of the Khorasan Razavi Province in spring and summer. The dust deposition was the highest in the areas at margin of the desert with low relief, sparse vegetation and high wind velocity. Monthly variations in dust fallout rates were related to some climatological parameters. There was a significant positive correlation between the average atmospheric airborne dust fallout in 12 sampling intervals, the maximum and minimum temperatures, and wind speed and there was a significant negative correlation between this parameter and relative humidity at P-value<0.05. These findings are closer to the results of Noroozi and Khademi (2015) (in Isfahan), Al-Harbi (2015) (in Kuwait), and Kaskaoutis, et al. (2016) (in the southwest of Asia). Furthermore, through the change of the direction in prevailing winds from east and northeast in dry months to the west and northwest, the rate of airborne dust fallout declined in most regions in the months with more precipitation, but not in the east of the Province where the area was exposed to the highest wind speed in spring and summer. It is noted that the increase of temperature causes a decrease in soil moisture; this issue is, in turn, considerably important in decreasing the speed of the threshold, which consequently increases the wind force and soil movement (Rahimi, 2015). In addition, rainfall and temperature can indirectly play an effective role in amount of the fallout rate through affecting vegetation due to the effect of these two parameters on the plant coverage (Makhdoum, 2006). The results of the analysis of climatic synoptic maps related to stormy days in the sea level pressure map showed that the establishment of the cyclone center in Afghanistan and the south of Khorasan, and the anticyclone center on the Caspian Sea and Turkmenistan cause heavy winds and dust storms in the region. Considering the geographical location of the Province (sharing borders with both Turkmenistan and Afghanistan) and the wind direction, it could be suggested that the sources of these storms are found in the surrounding areas. However, the determination of the source of the atmospheric suspended particles in Khorasan Razavi Province requires further study and more comprehensive laboratory analyses.

Recognition of climate and doing research about climatic requirements of farm plants can be regarded as main factors in the production process. According to the importance of the climatic fluctuations in rainfed productions, in this study effect of spatial distribution and temporal variation of climatic elements on wheat yield was studied in dry land farms of Kaleibar and Khodaafarin counties. For this, distribution of precipitation parameters was mapped in GIS environment and year-to-year variety of temperature and rainfall analyzed by drawing of charts. And thus with using wheat growing requirements (including desired climatic conditions), ability to meet the climatic needs of this valuable plant were examined. In addition by running of stepwise multivariate regression model between 16 meteorological parameters and average wheat yield, the role of climatic fluctuations in dry land wheat yield identified and the best predictive model determined. Final results of this study show the fact that the importance of each of temperature and precipitation factors differ according to different phonologic stages of wheat at the study region. Although it seems that the mean annual rainfall in study area appears desirable but large fluctuation from year to year as well as small amount of rain in Khordad(June) are the main limitations of rain fed wheat cultivation. Temperature in germination and grain filling stages are created ideal condition but at the flowering stage temperatures are cooler than optimal physiological threshold. The stepwise regression presented a model with 7 meteorological parameters that can be explain a significant impact of climate parameters on dry land farming wheat yield at 95% confidence level on the study region.

The reduction of river flows can be related to several natural and human factors. The reduction of entrance discharge to Urmia lake has significant rate on the reduction of the lake water level. The purpose of this research at the first step is to investigate the effect of climatic parameters such as precipitation and temperature and at the second step, to investigate the effect of human factors on the reduction of river flow of basins Sufichay and Mrdqchay located in the southeast of Urmia Lake.
Matherials and Climate and hydrological change trend were evaluated by Mann- Kendall classic and Modified methods. Then status of weather drought by SPI index and status basins hydrological drought was studied by SDI index in the time periods 3 and 12 monthly and the correlation of two droughts were examined by using Pearson correlation test. The status of vegetation by NDVI index and the status of soil moisture was studied by changing tasseled cap at past and present. Finally the discharge of rivers basin were compared at before and after dam construction and discharge of downstream of Alavian dam with precipitation elements.
The results show that both of the average and maximum discharge is reducing in the area during the statistical period. On trending of temperature and precipitation data both Kendall and Sen's estimator methods have The same results and many of data had non-significant trend and only a small percentage of data was significant. On The other side, from this low percentage the trend type on the precipitation data was different. However the temperature significance trend shows a rise on temperature. In examining meteorological and hydrological droughts the characteristics of o basins, SPI and SDI index have showed that both study scales indicate, two long periods of droughts during the same period and there was a significant relationship between two droughts. This relationship was for simultaneous 1 to 6 monthly delays. In the appraisal of the relation of vegetation status and soil moisture of basins in 1985 and 2006 the space of vegetation area has increased in both basins in 2006. The soil moisture has increased because of more absorption of rain water by the plants. The average comparison of discharge of Sufichay and Mrdqchay basins showed however that the discharge of two basins has declined after dam construction but the discharge of dam downstream shows more reductive variation. The multiple regression model also showed a strong correlation between basins downstream discharge with dam however, the correlation of discharge with precipitation had been non-significant.

climate is one of the most important parameters in agricultural products and it limits the amount of products . it is obvious that agriculture is in a great relation with surrounding environment and it is affected by the climate ,so climatic parameters in a long period can determine plantation algorithm and dispersion explanation of different kinds of plants . the main aim of this research is assessment of the procedure of changing in agriclimatic parameters which effects on barberry growth in Gonabad city. for this purpose we use daily information such as minimum and maximum temperature, raining, average temperature, proportional moisture, soil temperature, sunny hours, and average temperature , proportional moisture and soil temperature in the finishing day of phonology stages in Gonabad synoptic station of khorasan razavi province , and by using them climatic parameters volume in different probable levels are calculated . in next step Man Kendal test used to explore climatic elements procedure in different phonology levels of barberry product . results indicates that , between all climatic parameters which effect on barberry plantation The average temperature, soil temperature and sunshine hours speed have decreased in 5 percent level.

Climate is an important factor affecting human health. Structure and function of the human body is influenced by climate and reacts to changes in climate parameters. In this study, the relationship between climate parameters and mortality of urban population has been studied in Esfahan. Mortality data related to three diseases (cardio-vascular, respiratory and stroke) were collected form municipality of Esfahan during the 1384-1389 period and for the same period daily climate data were obtained from the meteorological organization of Iran. The relationship between mortality and climate parameters was studied with pearson correlation coefficient and T- test as a statistical examination of two population means was used to determine the seasonal variation in mortality. The results showed there was a direct correlation between mortality and some of climate parameters (humidity, pressure, and precipitation) while this correlation for sunshine and temperature (minimum, maximum and average) was reversed. Among three diseases cardiovascular showed the greatest sensitivity to climate parameters. T-test results also showed that there are significant differences (p<0.05) between seasons in disease mortality

Despite of technology progressives، natural hazards caused damage of world cities propertys and life، part of the damages related to adequate uncognition response to natural hazards. The dust natural hazard occurrence has attracted public attention in the recent years. Nonrecieption and attention to the natural hazards not only affected society economic، but also affected different societies life residents and due to abundant damages. THEORETICAL FRAMEWORK: Dust is one of the most natural hazard that located to attention of scientists in the different aspects. Assessment of dust is important in the most area of Iran، from the viewpoint of medical and sanitary problems، pulmonary respiratory and opttic diseases. The dust phenomenon as a global hazards occured in the dry and semi arid regions of earth. The Iran country because of location in the arid and semi arid belt earth، repeatedly exposed to different synoptic and local dust systems. Main reason of dust phenomenon، effect of wind force on area with particles and texture loom which suspened aerosol in the air and spread out regional climate condition distribution، recent occurrence of droughts increaseed this phenomenon. The paper has considered by analytical-statistical method، as first has considered and analyses the time distribution of dust phenomenon occurrence، then the relation of climatic parameters with dust occurrence analyze based on Pearson correlation coefficient and multiple regression، and then has drawn area seasonal and annual wind rose. Finally smart city conceptual model has identified as a solution for collation with this phenomenon. Dust disaster occurred appropriate to air warming in time period about five month from the April to August. Dust day highest occurred in the July and may months. This phenomenon has not similar distribution by the impacts of geography condition، in the Ilam city with higher height and latitude occurred the lower occurrences toward the Dehloran city. There aren’t significance relations between climatic parameters and dust days In the Ilam city، but in Dehloran station except significant relation between variables، the high determination coefficient (R2) show the main affection of climatic parameters in phenomenon occurrence. CONCLUSIONS & SUGGESTIONS: The creation source control of dust phenomenon is not easily removable and its required to national and transnational strategic plans. The representation of solutions is importance for compatibility and consequences and effects decreasing. By preparing the intelligent and electronic city infrastructure will be able the citizens to manage their self-daily time and exposure to dust phenomenon in lowest time.

Pterygium is one of the most common eye diseases causing astigmatism, eyesight limitation and some other skin diseases. Pterygium, with an outbreak of 22%, is of the highest rate of frequency of eye diseases in tropical areas. This study is to investigate the role of climatic factors spreading Pterygium during 1385-1390 in Mashhad. The data needed for the study has been gathered from the patients referred to Khatam Al-Anbiya Ophthalmology Department suffering from Pterygium during 1385-1390 in Mashhad, also the climatic data collected in Mashhad Synoptic Station has been used. At first the collected data were assessed by Minitab 16 software to have normal data, secondly the relationship between climatic factors and Pterygium has been analyzed by such different methods as statistical regression, Pearson correlation, multiple correlation, ANOVA model (ACF self correlation functions) as well as ultraviolet ray indication. The results of the study showed that monthly correlation between climatic elements of dust, sunny times, total radiation and wind speed with Pterygium is in its highest rates in Ordibehesht, Khordad, Azar, Dey and Bahman. Among the above parameters, the relationship between wind speed and sunny times with Pterygium has the highest correlation (r=0.89, p=0.01, & r=0.63, p=0.1). In addition, the results showed that climatic elements increase the disease rate according to the seasonal delay time, especially in the second half of the years.

In recent years, artificial models of weather generator parameters have extensively been applied in hydrological and ecological systems and also in the studies of climatic impact potential on agricultural ecosystems throughout the world. These models have been developed as a statistical technique for generating daily weather data when long-term data are not available. The purpose of this investigation was to evaluate the performance of three models of CLIMGEN, LARS-WG and Weather Man to predict at fine-scale and at meteorological stations’ scale for climatic variables including maximum temperature, minimum temperature, precipitation and solar radiation for the years of 2000-20009 in three regions of Gorgan, Gonbad and Mashhad. Firstly, daily weather data of each station from 1975-1999 for Gorgan and Gonbad and 1961-1999 for Mashhad were implemented in the models and the daily data for years 2000-2009 were obtained. For assessment of the mentioned models, the comparison of statistical indicators such as Root Mean Squared Error (RMSE), Model Efficiency (EF) and Determination Coefficient (R2) were used. The results obtained from comparing the monthly average of produced data during a ten-years period by models showed that temperature variable has been predicted better than other parameters by the three models. LARS-WG in Gorgan and Mashhad and CLIMGEN in Gonbad performed better to simulate the minimum temperature. CLIMGEN in Mediterranean climate of Gorgan and semi-arid climate of Gonbad and Weather Man in dry climate of Mashhad have simulated the maximum temperature better than the other models. Solar radiation variable by LARS-WG model in Mashad and Gonbad regions and by CLIMGEN model in Gorgan has been predicted by a more effective performance. Despite the differences among the outputs of the models, it seems that they can be applied in crop modeling and in the issues of climatic changes.

Crop growth and production at rainfed systems is related to climate parameters changes. Climate parameters changes influenced Crop growth and its production at rainfed systems. Assessing the effective parameters and planning for their managing and or arranging agronomic activity with those trend changes، which result to improving production baseline and prediction for future. Precipitation and temperature are more important climate factors، which influence crop growth and production. Assessment the components of these factors، lead to improving grain yield and rain water productivity. In order to estimation of climate-yield production functions، analyzed eight crop seasons data (1998-2006) of 25 climate parameters and rainfed wheat grain yields of two warm regions of Lorestan province including Kohdasht and Poldokhtar. By path analysis method separated correlation coefficient to direct and indirect effects. Statistical indicators such as mean absolute error، maximum absolute error، root mean square error، index of agreement and efficiency were used for evaluation climate models. Relationship between precipitation – yield and precipitation – water productivity، determined for this area. Results showed that in local and common models of production functions، the role of sunshine is very important. Sunshine influenced relative humidity and air temperature، and then affected on yield and rain water productivity. The local models necessary small input data but common model need more input data (Tmin، n، PWimter، PStart، PEnd، Tmin-abs، PAban، PAzar، PDay، PFar، POrd، Tmax-far.). Statistical indicators amounts، showed that، the climate models were suitable to yield predict at these regions. Rain water productivity of all regions determined for eight crop seasons، and amounts of maximum، minimum and average of rain water productivity were 0. 411، 0. 142 and 0. 269 kg per cubic precipitation، which its average was 8 percent lower than national average (0. 292 kg. m-3). We conducted the climate-yield models are useful tools to predict rainfed wheat yield and so to assist managers and farmers for making decisions in rainfed agronomic activity under climate parameters changes.

During recent years, dust storms are becoming very dangerous crisis with regional dimensions. Khuzestan province is one of these areas which is affected by this phenomenon. Meteorological and vegetation parameters play important roles in causing dust storms. In this paper, the relationship between spatial-temporal changes of these parameters and dust storm frequency (DSF) has been modeled. For this purpose, climatic data (wind speed, temperature, precipitation and humidity) and DSF were evaluated since 2000 to 2008. During these years, NDVI was extracted monthly by using MODIS images and then interpolating of climatic data was done by Kriging method. After preprocessing, data were pixeled to 18*19 matrix elements. A multivariate linear regression model (in terms of parameter) was estimated between climatic and vegetation parameters (independent variables) and DSF for each pixel (matrix element). Base on the models, except for month June, the accordance between predicted temporal values and actual values of dust events were too strong (Corr=96%). Soil, land use and vegetation land cover maps showed the high rate of potential of soil dispersion in south of Khuzestan which produced the most sources of domestic dust storms in this region. The accuracy of model was evaluated for 10 classes of soil, separately. The highest and lowest accuracies were for salty and marshes and sandy land, respectively. So, destruction of vegetation cover effectively cause increasing domestic source dust storms in Khuzestan and saline and alkaline soils intensify the emission of dust in the atmosphere.