The ozone layer, as a life protective shield on the Earth, has attracted the man’s attention from various aspects. For the same reason, different dimensions of the ozone layer have been studied by researchers. The changeable amount of total ozone is affected by the sun, atmospheric elements, and climatological photochemical activities. Hence, the major amount of ozone is affected by atmospheric instability in the upper troposphere, and the atmospheric instability is united through the teleconnection patterns with climatic indices. Therefore, the total amount of ozone is connected to the climatic indices. The aim of this research is to study of climatic indices on the total ozone (TO) oscillations in Isfahan station.

Introduction: Teleconnection is one of the features of the climate on a global scale. Teleconnection patterns represent large changes that occur in the pattern of atmospheric waves and tornadoes and affect the pattern of temperature, precipitation, the direction of showers and the position and intensity of tornadoes in large areas.   Objectives: The aim of this study was to investigate the effect of these patterns on temperature series in Zahedan.Methodology: In this regard, minimum temperature, maximum and average temperature statistics of Zahedan station during the period of 1987-2019 on a monthly scale as well as standardized data of teleconnection patterns during the mentioned period, were used. Pearson correlation and multivariate regression tests were used in this regard.Geographical Context: The geographical territory studied in this research is the city of Zahedan.Results and Discussion: The results indicate that there is a significant relationship between teleconnection patterns and the average temperature of Zahedan. Among these, NTA, AMO and TNA patterns had the greatest effect on the average temperature of Zahedan. The correlations were direct, and only the NAO pattern was inversely correlated. The maximum and minimum temperatures of Zahedan also showed the highest correlation with the patterns located in the North Atlas. The maximum temperatures in March and October and the minimum temperatures in March and August had the highest correlation with the North Atlantic patterns.  Conclusion: In general, it can be said that the patterns located in the North Atlas, more than other patterns, have affected the temperature series of Zahedan and especially its average temperature.

Aims & Backgrounds Drought is a natural feature of an area and its occurrence in each region can lead to economic, social and environmental losses. The aim of the present study was to investigate the relationship between the teleconnection patterns with drought in the Qara-Qom basin. Methodology The precipitation data of 30 rain gauge and synoptic stations and the data of 32 numerical indexes of teleconnection from NOAA site were obtained during 1987-2013. The data of standardized precipitation index in the 9 to 48-month scale were classified by factor analysis and the stations with similar behavior were identified in the study area. Then, the relationship between the average drought index of each area with each of the teleconnection patterns was evaluated simultaneously with a delay of 6 and 9 months through the correlation statistical method. Findings The multivariate ENSO index, the decadal oscillation of Pacific ocean, southern oscillation, Nino 4, ¾ and 3 had the most significant correlation with the standardized precipitation index scales. Also, there was a direct correlation between the 6-month delayed drought index (With four factors of drought index) with Nino 4, 3/4 and 3, multivariate ENSO, Madden Julian oscillation in the regions of 20° , 70° , 80° , 100 ° east, and there was a significant inverse correlation between the 6-month delayed drought index with the east pacific index, the southern and Madden Julian oscillations in the regions of 160° East, 120° and 40° West. Four factors of the 9-month delayed drought index (total basin stations) had a significant inverse correlation with the east Pacific index, southern and Madden Julian oscillations in the regions of 120° and 40° West, and it had a significant direct relationship with the index of Nino 3, the multivariate ENSO and the oscillation of Madden Julian in the regions of 70° , 80° and 100° East. Conclusion There is a relationship between the teleconnection patterns and droughts in Qara-Qom basin.

Generally, Climatic extreme events, like the heavy rainfalls and sudden changes cause the greatest range of damages to water resources, agricultural and even human daily life. Therefore, correction and regular monitoring reduces their negative effects. Climatic signals represent changes of between temperature and pressure in ocean that they are one of the most influential parameters on climatic patterns. This study evaluates the effects of large – scale climate factors on rainfall extreme indices in Sistan-Baluchestan province as symbol of arid land in Iran that it has sever climatic oscillations. In order to at first step we use data of daily rainfall 6 synoptic stations at 1987-2014 period from meteorological organization and 19 Teleconnection indices from NCEP/NCAR. Then we calculated extreme indices. In continue correlation of extreme indices and teleconnection calculated. In next step we analyzed affecting teleconnection by regression model. The result of the correlation between teleconnection indices and extreme rainfall indices showed that TSI, TNI, AO, WP, WHWP, TNA, NINO1, EA, NINO4, PDO, PNAو NAO have correlation with rainfall extreme indices but this effects are different in station to another as in Khash station the most correlation occur with R50 and in Chabahar station occur with R10. So determined that teleconnection identify about 30 percent of changes.

Introduction The climate of a region is influenced by many factors, some of which are planetary and some are regional and local. Teleconnection patterns are the origin of anomalies. Therefore, revealing the relationships between climatic parameters and teleconnection patterns is important for further understanding of climatic fluctuations and variability in each region. The purpose of this research is to investigate climate anomalies using Teleconnection patterns are the origin of anomalies that are seen Therefore, revealing the relationships between climatic parapatterns. For this purpose, the rainfall data of two observation stations (Khorram-Abad and Kermanshah) were collected during a period of 68 years (1951-2018). In this research, two types of data were used. 1- The monthly rainfall data of two synoptic stations of Khorramabad and Kermanshah were obtained from the National Meteorological Organization. 2- Data related to remote connection patterns including: Polar Oscillation (AO), North Atlantic Oscillation (NAO), Scandinavian Pattern (SCA), East Atlantic Pattern (EA), East Atlantic-West Russia Pattern (EA/WR) ), the North Tropical Atlas pattern (TNA), the Polar-Eurasia pattern (POL) and the Meridian Wind pattern (AMM), the Southern Oscillation (SOI), the combined pattern (Best) of the East Pacific-North Pacific Oscillation (EP/NP), Water surface temperature in Niño 1 and 2 (Niño 1+2) and water surface temperature in Niño 3 and 4 (Niño 3.4)) were obtained from the NOAA website.   Materials and Methods Analytical statistics and inferential statistics methods were used to determine the effect of Teleconnection indicators on rainfall in the region. First, the rainfall time series of each station was tested for significance using the Anderson-Darling test at the 95% confidence level. Also, to evaluate the condition of independence of time series, the sequence test was used. Then, the Teleconnection indices were divided into two groups. Atlantic Ocean-based indices (AO, NAO, SCA, EA, EA/WR, TNA, POL, AMM) and Pacific Ocean-based indices (SOI, Best, EP/NP, Nino 1+2, Nino 3.4) And their interaction. In most statistical materials, parametric tests such as variance analysis, correlation analysis, regression analysis, etc., are based on the assumption that the measurements within each statistical population have a normal distribution and an equal variance-covariance structure.The hypothesis of establishing a normal distribution is related to the distribution of the studied population and not the samples.In order to be able to accept this hypothesis, that hypothesis must be substantiated in theoretical fields, that is, the values must be symmetrically centered around the average number. In this regard, data that have a skewness (lack of symmetry) or are strongly integrated in a part of the measurement scale, affect the variance-covariance between the variables. Analysis of variance is one of the parametric methods that evaluates the relationship between a dependent variable and an independent variable.In this approach, the independent variable is considered as the agent variable and the dependent variable as the response variable. In order for the results of the analysis of variance to be valid, several assumptions must be considered when applying its formulas. The first assumption is that the observations are independent. It means that each observation is uncorrelated with another observation. The second assumption is that the observations are normally distributed. That is, all observed measures of central tendency, including mean, mode, and median, should be the same. The third assumption is that the variance is homogeneous. That is, the sizes of the distribution of scores should be determined. This assumption is called homogeneity of variance. Therefore, before applying the statistical tests, first, the time series of monthly rainfall of Khorramabad and Kermanshah stations were tested for significance using the Anderson-Darling test at the 95% confidence level. If any of the precipitation time series is not normal, we tried to normalize that time series by using Johnson transformation functions. If these functions were not able to place the precipitation time series in the normal range. Kruskal-Wallis method, which is equivalent to non-parametric analysis of variance, was used to test the precipitation of these non-normal time series. In the following, in order to find out whether the average monthly rainfall of Khorramabad and Kermanshah synoptic stations has changed during the different phases of the teleconnection patterns, or in other words, whether the average monthly rainfall in the west has undergone changes due to the positive or negative phase of these patterns, first the values The standardized index of these patterns was divided into three levels: neutral, positive and negative. Then one-factor analysis of variance and Kruskal-Wallis test were implemented on these three levels as factors and the time series of monthly rainfall as the response variable.   Conclusion The distribution values of Kruskal-Wallis statistics for the months of October and September and the values of the analysis of variance statistics for other months of the year revealed that the influence of the indices based on the Atlantic Ocean has less homogeneity and order than the indices based on the Pacific Ocean. In a way that the phase change of the Pacific Ocean indicators has caused a significant change in the rainfall of October and November in Khorramabad and October in Kermanshah. If the influence of the patterns based on the Atlantic Ocean does not have such an arrangement. In general, the patterns of the Atlantic Ocean have caused a significant change in precipitation mainly in the winter season, while the patterns based on the Pacific Ocean have had a significant effect on the precipitation in the autumn season. In this regard, the East Atlas-West Russia pattern had the most significant effect on the precipitation of these two stations, while the polar oscillation pattern, the Eurasia polar pattern, and the meridian temperature pattern caused a significant change in precipitation in only one month and one station. Also, the Scandinavian pattern has a significant effect on the October rainfall in Khorramabad, January, March and December in Kermanshah. On the other hand, the East Atlas pattern and the North Tropical Atlas pattern have had a significant effect on February rainfall in Kermanshah and October in Khorramabad. On the other hand, the East Atlas pattern and the North Tropical Atlas pattern have had a significant effect on February rainfall in Kermanshah and October in Khorramabad. The East Atlas and Scandinavian patterns have a significant effect on the October rainfall in Khorramabad and Kermanshah. In general, the patterns of the Atlantic Ocean have caused a significant change in precipitation mainly in the winter season, while the patterns based on the Pacific Ocean have had a significant effect on the precipitation in the autumn season.

Rainfall and mean temperature are the most important meteorological parameters in determining distribution of other meteorological variables and also in climatic classifications. In addition, they have undeniable effects on human, natural and especially agricultural activities. Therefore knowing the value, variation and prediction of these parameters could result in precise management in different sectors. This research was done for the assessment of teleconnection indices, which affect the two mentioned parameters in Mashhad during the period of 1956-2010. The stepwise regression model with limited input was used for training and also evaluation data to derive monthly and seasonal prediction models. The statistical results showed that these models have the suitable performance to predict the rainfall and temperature parameters. In general, this performance was more appropriate for monthly models than seasonal ones, and also for temperature than rainfall.

External source of weather signals is also called teleconnections that can change weather conditions and thus affect groundwater resources. The purpose of this study is to predict the effect of teleconnection patterns on groundwater level fluctuations in Garmsar plain. Data of observation wells, climatic parameters of the study area, as well as 16 teleconnection indices from 1993 to 2016 were used for this study. Gamma test was used to analyze inputs sensitivity and so determine the optimal combination of inputs. Modeling was performed with multiple regression as well as multilayer perceptron artificial neural network (MLP) with two algorithms of Levenberg-Marquardt and Bayesian. Sensitivity analysis results of model inputs with gamma test showed that among the climate parameters of the region, maximum temperature of Firoozkooh station and also teleconnection indices of SOI, EA, NP and WP had the most influence among the selected inputs. Also, the best model is the neural network method with Bayesian learning algorithm, that in the model testing stage in Sardareh well, the MSE and the R 2 were 0. 37 and 0. 9 respectively. In well 26, these values were 0. 06 and 0. 74, respectively. Also, results indicated that the use of teleconnections indices to predict groundwater level fluctuations can have effective role in error rate reduction.

One of the most important climatic elements that is influenced by teleconnection patterns is temperature and precipitation, both of which are the most influential factors in the study of tourism comfort climate. The purpose of this study is to investigate the climate of tourism comfort in Gilan province during the years 1980 to 2016 using the UTCI model and also to investigate the relationship between tourism comfort climate of Gilan province and Teleconnection patterns. The climate comfort of Gilan province is one of the atmospheric signals. Investigating this relationship can help us plan properly for tourism development in this province and also find the suitable location. Using the Mann-Kendall trend test, the obtained results showed that in the last 37 years, the value of the UTCI index has decreased in July; also the extreme heat stress in this month has decreased. However, in other months of the year, no specific trend has been seen for this index. Also, the correlation between the indicators of tourism comfort climate in the province with Teleconnection patterns which had been estimated through the Pearson correlation coefficient showed that out of 22 models understudy, nine models including TNA, NTA, SOLAR FLUX, NCP, SOI, NAO, MOON SOON, AMM, AMO were directly or inversely related to UTCI in different months of the year.

The term "teleconnection pattern" refers to a recurring and persistent, large-scale pattern of pressure and circulation anomalies that span vast geographical areas. Teleconnection patterns are also referred to as preferred modes of low-frequency (or long time scale) variability.Teleconnection patterns reflect large-scale changes in the atmospheric wave and jet stream patterns, and influence temperature, rainfall, storm tracks, and jet stream location/ intensity over vast areas. Thus, they are often the culprit responsible for abnormal weather patterns occurring simultaneously over seemingly vast distances. 14 teleconnection patterns have been recognized in Northern Hemisphere. In this paper we attempt to detect the relationship between monthly temperature of Iran and the teleconnection indicies. we used mean monthly temperature data and monthly index of each teleconnection pattern for the period of 1951 through 2003.teleconnection pattern indices are gathered from the www.cpc.noaa.gov and  temperature data for 338 stations of Iran are gathered from www.irimet.net.In this paper we used linear regression technique .We regressed each index against the monthly temperature for all 338 stations for each month during the period of record (1951 trough 2003). This study attempts to detect significant relationships for 14 indices using Matlab7, Then the results plotted in geographic in G.I.S environment.This study showed that none of the indices could explain a great deal of temperature variations of a large member of stations. Meanwhile some indices in some months could explain some part of temperature variations of some stations.