جستجوی مقالات مرتبط با کلیدواژه « Mann-Kendall » در نشریات گروه « جغرافیا »

Precipitation anomalies, especially drought and its changes are among the most important topics in climatology. The current study was carried out to regionalize drought events and evaluate the changes in their extent in annual, seasonal and monthly time scales. For this purpose, EAR5 monthly rainfall data and the RAI drought index were used. Hierarchical cluster analysis based on Ward's correlation-integration distance Mann-Kendall's test and the slope of the regression line were used to extract spatial clusters and their changes. The number of spatial clusters (areas) of co-occurrence of drought in the rainy season and months is wider and more homogeneous than in the less rainy months such as the summer season. Certain geographical-climatic areas such as Southeast, Center, Northwest and West-Southwest are seen most of the time. The annual drought changes in none of the areas show a significant trend, which could be due to intra-seasonal and monthly contrasts in drought changes. So in winter and spring (the main rainfall period of the country), an increasing trend was observed, and on the other hand, in autumn, a decreasing trend of drought was observed. On a monthly scale, the most obvious increase trend has occurred in the two main months of rainfall in the country, namely January and March, and a decrease in November. The results of the research can indicate the temporal shift of rainfall or the change in the country's rainfall regime

The main goal of the current research is to analyze the temporal changes in air quality in these areas based on an index of both types of events called the Pollution Dust Storm Index.

 This study calculated the PDSI using the frequency of local and extra-local dust events. The Mann-Kendall test was used to evaluate the trend of temporal changes in this index at different time scales.

 The highest dust pollution in the analyzed statistical period belonged to the cities of Zahedan, Chabahar, Nehbandan, and Yazd, and the lowest air pollution was in Baft, Shahrood, and Shahrbabak stations. The significant incremental changes in dust events occurred for most of the stations in June. On a seasonal scale, maximum and minimum dust pollution occurred in spring and autumn, respectively. The increasing trend of dust occurrences in the spring season and their decreasing trend in the summer season was observed for most of the stations. 

 The findings of evaluating the trend of changes in dust occurrences based on the PDSI index in dry areas of the country, which are affected by dust with different frequencies and intensities throughout the year, can be used to identify sensitive areas and provide necessary measures to prevent and reduce adverse effects caused by dust events.

Innovation:

 In addition to local dust events, extra-local events also impact the air quality of dry areas. Analyzing changes in the PDSI based on both types of events can enhance our understanding of air quality in these regions. This study aims to analyze air pollution changes using this index, which has not been done before for dry areas. The findings can help identify areas with higher air pollution levels and lead to more effective solutions to improve air quality in arid regions.

This article was written with the aim of predicting the process of climate change in Tehran. In this article, the status of rainfall and temperature (minimum and maximum) of Tehran was reviewed at geophysical, Shemiranat and Mehrabad synoptic stations during the 1992 to 2018 period and was used to identify the existence of leaps and revelations of the years of mutation. It was also used to predict climate elements in Tehran using CMIP5 data and Lars model for three scenarios of RCP2.6, RCP4.5, RCP8.5. Results of the Time Time and Rainfall Series Trends of the Three Stations Investigated in Tehran, using my Kendall process analysis test, showed that in the case of none of the climatic factors in the three stations under investigation, a significant change in P_Value = confidence level = 0.05 did not occur. But many annual mutations and fluctuations were observed in the temperature and rainfall series. Also, the results of the climatic parameters of the minimum, maximum and precipitation temperature parameters showed that the minimum temperature and maximum by 2050 compared to the base period (1992 to 2018) in all three carbon dioxide emission lines RCP2.6 , RCP4.5, RCP8.5, will be significantly increased in all three studies. But rainfall will be significantly reduced by 1.7 mm per month compared to the base period of 1992 to 2018 in all three carbon dioxide emissions in all three stations

Nitrogen dioxide is considered one of the important indicators for evaluating the air quality of cities, therefore, identifying the areas contaminated with this pollutant is very important. One of the sciences and technologies that can help urban environmental experts to identify these areas in the shortest time and at a lower cost is satellite remote sensing. Currently, satellite remote sensing is a useful technology for measuring atmospheric pollutants at the global, regional, and urban levels. Therefore, the present research has identified and investigated the temporal-spatial distribution of nitrogen dioxide gas during the spread of Covid-19 using Sentinel-5P satellite data in the Shiraz metropolis for 24 months (2019 and 2020). Based on the results of this research, the highest monthly average values of nitrogen dioxide gas in 2019 and 2020 are related to the autumn season. In addition, district 2 of Shiraz was identified as the most polluted area in the two years studied. In addition, after analyzing the parameters of wind, precipitation, and temperature, it was found that the wind factor with a correlation coefficient of -0.638 at a significance level of 1% compared to other climate factors had the greatest impact on the change in nitrogen dioxide gas values. The Covid-19 crisis also played a role in changing the amount of nitrogen dioxide gas in 2020 compared to 2019 every month with its impact on the reduction of traffic and urban traffic. The pattern of changes in the average nitrogen dioxide gas related to satellite data in the studied years had a decreasing trend, which was consistent with the pattern of changes in the values obtained from the pollution monitoring station. The results of this research can be useful in urban livability and crisis management.

Currently, agriculture is one of the most important economic sectors of any country. One of the basic ways to develop and promote agricultural activities in any country is the optimal use of land, according to ecological conditions. Such a development requires to know the various factors that are involved in it. Therefore, researchers pay special attention to land use and based on ecological-agricultural models, identify, evaluate, and assess the ecological resources of land with appropriate methods for specific purposes. Weather is one of the basic environmental factors that control all aspects of life. Among the climate elements, temperature and precipitation play a decisive role. Temperature, as an indicator of the intensity of heat, is one of the basic elements of knowing the weather, and due to receiving the sun's energy from the earth, it undergoes many changes, which in turn causes extensive changes in other meteorological elements. Investigating the impact of weather factors on the performance of agricultural products is extremely important and the production efficiency of agricultural products is largely related to climatic conditions Climatic features in the long term have led to determining the cultivation pattern and justifying the distribution of different plant species. The present study was conducted to evaluate the trend of climatic parameters on the initiation of barberry tree germination in Iran

The research area, the areas prone to barberry tree cultivation in Iran amount to 1.356858 square kilometers, equivalent to 22.1%, and the eastern regions of the country include the provinces of South Khorasan (Qain, Birjand), Fars (Shiraz, and Abadeh), Hamadan, Markazi, Isfahan, Chaharmahal, Bakhtiari and Kerman are the best places to grow this crop. Also, some of the northwestern provinces of Iran, along with Zahedan and the southern provinces of Razavi and Western Khorasan provinces (Saqez, Sanandaj, Kermanshah, and Khorram Abad) are relatively suitable for barberry cultivation. In this research, using the non-parametric Mann-Kendall method and the Slope Sense test, the trend of changes in the elements of sunshine hours, average humidity, average temperature, minimum temperature, maximum temperature, the number of freezing days, and total rainfall in 19 stations of the country in 30 years. 1990-2020) was done on the growth of barberry and its output was drawn in the form of tables, graphs, and trend maps in the Arc GIS environment. The results showed that six main phenological stages occur in the BBCH scale in barberry trees. According to the location, the south of Razavi Khorasan and the center towards the northwest of the country are the best areas for barberry cultivation. The growth period according to climatic conditions and topography lasts from the beginning of April to the end of November.

To analyze the trend of climatic parameters in the barberry cultivation areas in Iran, the statistics of Mann-Kendall tests and age slope estimator were used, and the significance of these statistics was examined at the confidence level of 99% and 95%. Estimating the slope of the trend line with the age estimator showed that the slope of the trend line of the total hours of sunshine in the germination phenology stage has the most changes in the station of Yazd (0.33 hours) and Tabriz (0.1 hours). The trend analysis of the average relative humidity parameter showed that a significant decreasing trend can be seen at the 95% confidence level in the stations of Shahrekord, Khorramabad, Abadeh, Zanjan, Fasa, Birjand, and Torbat Heydarieh. In the stations of Qain, Arak, Zahedan, Yazd, Kerman, and Kermanshah, there is a significant decreasing trend in the confidence level of 99%. The number of changes in the average temperature during the germination period of the barberry tree was obtained based on the SEN's slope. Have had. The analysis of the trend of minimum temperature showed that all the stations except the cities of Shiraz, Saqqez, and Sanandaj have an increasing trend at a significant level of 5%, the rest of the studied stations have an increasing trend at a significant level of 1%. Estimating the slope of the trend line with the age estimator of the maximum temperature parameter showed that the slope of the maximum temperature trend line in the germination phenology stage, in Zahedan station (0.37°C) and Saqez (0.06°C), respectively, has the highest and The least changes. The analysis of the time series trend of the total rainfall showed that except for the stations of Tabriz, Khorram Abad, and Shahr Kurd, there is a significant decreasing trend at the level of 5%, and no special trend was observed in the rest of the stations. Examining the number of frost days by estimating the slope of the trend line with the age estimator showed that the slope of the trend line of the average number of frost days in the germination phenology stage has the most changes in Tabriz station (0.03 days per year). The results and achievements of this are important for raising awareness about the role and importance of climatic conditions in choosing species compatible with the climate of each region, as well as providing a model for correct management and risk of horticultural products.

The purpose of this study is to determine the long-term variations in rainfall data as well as to identify wet and dry periods of 35 synoptic stations in Iran. In order to know the variation of rainfall in studied stations, average maps, coefficient of variation and skewness were drawn. Then, using the Mann-Kendall test, the significance of the trend on each station was tested at 95% confidence level. Finally, wet and dry periods were identified by using 20% high and low extreme rainfall during the 50-year study period. The results show that the general model of the country's regime is that the rainfall levels from the north to the south-east and from the west to the east of the country are reduced. The lowest values of the coefficient of variation and skewness are related to the northern regions especially the Caspian seaside and the highest amounts are in the southern regions, especially in the south and south-east. In general, the results of the Mann-Kendall test show that rainfall data in the seasonal scale, with the exception of several synoptic stations, do not show a significant trend. Most wet periods occur in the spring and the lowest in summer and the highest dry periods occur in the autumn and the lowest in spring. The number of droughts in the cold periods is significant. Also, the frequency of occurrence of dry periods is more than wet periods.

Climate change is considered as one of the environmental challenges in recent decades. Climatologists have evaluated the behavior and change of climatic elements to identify weather change and its importance to the structure of the Earth's weather in recent years. Trend is one of the most critical components of a series, which is very practical in climate to investigate the long-term orientation of time series. Outgoing long Wave Radiation (OLR) is one of the basic variables of weather, as well as the core component of the earth radiation budget (Whitburn et al., 2021: 1. Scherrick et al., 2018: 1), which is known as an essential parameter in applications for cloud identification and precipitation estimation. Therefore, it is necessary to study Outgoing long Wave Radiation trends at different temporal and spatial scales. Mann-Kendall test is one of the widely used non-parametric tests, which has been applied in climate studies, especially in examining the trend significance (Gauss and Trajkovic, 2013: 172. Nelson, 2001: 57). Kefayat Motlagh et al. (2018: 128) indicated that the trend of earthlight radiation is increasing by 0.4 watts per square meter in each decade, while the trend of Iran's earthlight radiation is more than three times (1.4 watts per square meter) the global trend in the same period. Sari Sarraf et al. (2015: 33) investigated the effects of global warming on the cities’ climate in the Urmia Lake basin using the Kendall method and the least-squares error. They concluded that the average rainfall in the whole region decreased by about 4 mm per year. Chu and Wang (1997: 636) examined the trend through Mann-Kendall statistics to find climate change in convective precipitation in the western Pacific and Indian Oceans from Outgoing long Wave Radiation. They found a significant decrease in OLR in the tropical central and western Pacific and a large part of the Indian Ocean, while the largest increase in OLR over time was in North Australia. In this study, the trend and changes were investigated using the non-parametric Man Kendall method, the amount of changes was determined by Sen's Slope method, and hot spots analysis was performed by Jay statistical method given. In addition, spatial and cluster analysis was performed on the average data and seasonal variation coefficient due to the importance of Outgoing long Wave Radiation at different temporal and spatial scales.

Iran, with an area of 1648195 square kilometers, is located between 25 to 40 degrees north latitude and 44 to 63 degrees east longitude. The data of the Atmospheric Infrared Sounder (AIRS), Aqua satellite, were used to measure Outgoing long Wave Radiation for a statistical period of 17 years (01/07/2002 to 01/07/2019). MATLAB, ArcGIS, and SPSS software were used for calculations and maps. First, the average monthly data maps of Outgoing long Wave Radiation were prepared, and then, the standard deviation parameter was used to show the data dispersion. Moreover, the Mann-Kendall test was used to determine the trend of outgoing long wave radiation on each cell in Iran, and the slope of the data series trend line was calculated by Sen's Slope estimator method. Spatial variations of outgoing long wave radiation were calculated over time as spatial behavior using hot spot map analysis.

According to Stefan–Boltzmann law, the Earth's surface and atmosphere emit energy in waves in proportion to their temperature. These waves propagate in the range of long wavelengths, i.e., between 4 and 100 microns given the normal surface temperature and atmosphere (Kaviani and Alijani, 2000: 94). According to the maps, the average long-wave radiation fluctuates between wet and dry seasons as well as geographical offerings, and its amount is higher in the dry season and the southern regions of the country. One of the reasons for the maximum outgoing long wave radiation of southern Iran in early spring is the angle of vertical radiation of the sun and the clear sky, which receives more energy than the latitudes, and the amount of energy output is more in the south of Iran than in the north. The outgoing long wave radiation increases gradually due to the decrease in cloudiness, and more energy is received in longer geographical areas gradually, in May and June, with the onset of summer as the day length increases. The ingoing and outgoing radiation becomes more uniform throughout the regions of Iran, except for the mountainous areas and the coasts. According to the results of cluster diagrams in the three seasons of spring, autumn, and winter, the radiation patterns of the basins are similar to the latitude and mountainous areas in Iran. The largest cluster in spring belongs to the south of the Alborz Mountains and the west of the Middle Zagros Mountains depending on latitude and sunny slopes. The highest uniformity in all seasons is located in the southwestern quarter of Iran, and Haraz heights in southern Iran are distinguished as a cold spot among the surrounding basins. Examination of the trend by the Mann-Kendall method showed no significant trend on an annual scale, but monthly and seasonal anomalies are quite evident. The descending trend of long wave radiation can be confirmed only in May and September in some parts of the country, and the dominant trend in most months of summer, autumn, and winter is increasing in most parts of the country, including northern offerings. The results of the G-statistic study also show the changes of hot spots towards northern offerings.

The trend of 17 years of outgoing long wave radiation of the earth (2003-2019) was investigated in monthly, seasonal, and annual time scales using non-parametric Men-Kendall test and hot spot statistics (G). Changes and abnormalities of long wave radiation were observed on a monthly and seasonal time scale in most parts of the country. These changes can be due to changes in the amount of energy input, cloud cover, and the type of clouds, aerosols, atmospheric compounds, such as moisture from global warming and other greenhouse gases. In addition, changes in land cover such as vegetation, forests, water resources, salinities, and sand dunes can influence the sensible heat and change of ground wave radiation due to the amount of moisture, which needs further investigation in this regard.

Applying climatic indices introduced by the Expert Team on Climate Change Detection and Indices is one of the most widely used methods to detect climate change. In present research, daily temperature and precipitation data of Zabol, Zahedan and Iranshahr synoptic stations were applied during the period 1966-2015 to detect the occurrence or absence of climate change. To this end, 8 precipitation and 2 temperature related indices were used, Mann-Kendall and slope estimator methods were applied to determine trend and magnitude of trend, respectively. Results suggested non-significant increasing trend in monthly maximum value of daily maximum temperature and daily minimum temperature. The studied indices related to precipitation are also decreasing without trend significant in all over the province. Consecutive dry days index of is decreasing without specific trend at Iranshahr station, but it increasing without specific trend at other two stations. In addition, Consecutive wet days index has a significant decreasing trend at Iranshahr station while it has non-significant decreasing trend at Zabol and Zahedan stations. The 1-day and 5-day maximum precipitation amount indices are decreased that is no trend observed for the 5-day maximum precipitation at Zahedan station. It can be stated that the climatic indices related to temperature and precipitation are increasing and decreasing, respectively in the study area. Overall, it can be concluded that the happened changes and fluctuations in the study area are not related to climate change phenomena due to the lack of significant trends in the majority of used indices. However, understanding these changes can greatly help decision makers and urban and regional planners, especially in matters related to metropolitan development and agriculture, and so on.Extended AbstractIntroductionRegarding the detection of climate change, the long-term series trend of climate parameters such as precipitation and temperature need to be studied. A major part of climate change studies has been conducted through analysis of precipitation, temperature, pressure, humidity time series and their positive or negative trends. Researches indicated that, atmospheric parameters are strongly influenced by the global warming, greenhouse gases, surface phenomena (ocean and land temperature increase), urbanization and urban heat island (Ben.Gai et al., 2001; You et al. 2011). Analysis of time series is an appropriate method used for mathematical modeling, prediction of future events, trend detection of climatic data and missing data reconstruction. Generally, it is said that the trend in the climate indices time series may result from a normal gradual change, climate change or human activities effects (Brooks and Carruthers, 1953). It should be noted that, confirming the existence of a significant trend in time series related to the precipitation or temperature (for example extreme climate indices) cannot be solely a decisive reason for the existence and occurrence of climate change in a region, but it reinforces the assumption of the event, because there are many parameters associated with the control and operation of atmospheric systems (Serrano et al. 1999: 2894). The Mann-Kendall test is one of the most common and widely used nonparametric methods for time series analysis, and it is used to identify the trend changes. This method is widely used to analyze hydrological and meteorological time series trend. The Mann–Kendall test is used for trend analysis in ETCCDI workshops.MethodologyExpert Team on Climate Change Detection and Indices (ETCCDI) introduced 27 climate indices to study the climatic parameters (Peterson et al. 2001), consisting of 16 indices for temperature and 11 indices for precipitation. In the present study, climate indices including RX1day, RX5day, PRCPTOT, CWD, CDD, R20, R10, and R95p were used for precipitation, and TXx, TNn were used for temperature, according to the objective of this research. All of these indices were calculated by the RClimDex software package. The indices were calculated for three synoptic station in the area, and then the time series was attained associated with each index.  The Mann-Kendall test was used at 90, 95, and 99 ⁒of confidence level for time series indices at 10, 5, and 1 ⁒level of significance, respectively, and according to the Mann-Kendall test Z-statistic, the ascending and descending trend of each index were determined over time. Subsequently, the gradient of trend line was determined by Sen’s slope estimator. Also, the graph of climatic anomalies of indices was drawn compared to the long -term average for these synoptic stations over the time. The Sistan and Baluchestan province is licated in Southeast of Iran, between 25° 04ʹ to 31° 29ʹ north latitude and 58° 55ʹ to 63° 20ʹ east longitude with 178431 KM2 area. In this study, to achieve precise results, daily data on temperature and precipitation collected from three synoptic stations including Zabol, Zahedan and Iranshahr in Sistan and Baluchestan was used during a 50-year period (1966 -2015).Result and DiscusionThe results indicate that the indices refer to the precipitation including PRCPTOT and R95p have a decrease trend during statistical period and the largest positive and negative anomaly the PRCPTOT index were in 1982 and 2001, respectively, compared to the long-term average, also about R95p occurs in 2007 and 2001. The anomalies related to rainfall intensity including RX1day, RX5day, R10 and R20 also have a decreasing trend. Regarding the temperature indices, it should be noted that temperature has been increasing over the years studied. The TNn anomaly is increasing with a relatively steep incline. This means that the cold days are decreasing during the desired years and generally the minimum temperatures have been followed by an increasing trend. In contrast, the anomaly of TXx has been almost constant trend and does not show much variation. The trend of PRCPTOT, RX1day, R10 and R95p are non-significant decreasing trend at all three stations. Regarding the CWD index, the results showed a decrease in all station, with a significant decrease at 95% confidence level at Iranshahr station and non-significant at the other two stations. In addition, the CDD index increased in Zabol and Zahedan and showed a non-significant decrease in Iranshahr. About the trend of temperature indices, it was found that the trend of TNn was non-significant increasing in Zahedan and Iranshar and there was no trend in Zabol. Also, the TXx index increased without trend in Zabol and Zahedan stations and there is a decrease trend at the 90% significant level in Iranshahr.ConclusionThe present study investigated the occurrence of climate change in Sistan and Baluchestan province using daily temperature and precipitation. For this purpose, was used of 8 indices for precipitation and 2 indices for temperature from ETCCDI. The result showed that the indices under study have changes and fluctuations, but in the vast majority of cases the changes were short-term climate fluctuations and trends are not significant during the time. The study indicates that overall the amount of rainfall decreased in the whole region, especially in the northern part of the province, but the intensity of precipitation decreased in the central and southern regions more than in other areas. As for the temperature the whole region shows an increase in temperature. Occurrence of changes in the region causes dramatic changes in increasing energy and water demand as well as changes in the region’s water resources. Therefore, the results of this study and research like this can provide valuable help and guidance for planners, decision makers and policy makers in adopting strategies to cope with these changes, both in term of risk management and access to renewable and low-cost energy.

The presence of trends in rainfall and temperature can be evidence of climate change. There are different methods for examining changes and trends in temperature and rainfall time series, which are divided into two categories: parametric and non-parametric statistics. The linear regression method is a parametric category and the most common non-parametric method is the Kendall method. The aim of this study is to study the change of some climatic elements in the north and northwest of Kerman province from normal. The time period studied in this research is a 20-year period that occurs between 1999 and 2019. To study the trend of changes in meteorological parameters (average temperature, rainfall and wind speed) in Kerman province and in Anaar, Zarand, Sirjan, Shahrbabak stations, Man-Kendall and least squares regression methods were used. The results of regression of trend line slope show that for moderate temperature is a positive trend for all stations and only Shahrbabak station has a negative trend (-0 /0019)) about the rainfall parameter for the whole province has a negative trend that shows a negative trend. In the region is declining and we are moving towards droughts. Regarding wind speed, the trend is positive for Pomegranate, Zarand, Sirjan and Kerman stations and ShahrBabak station is without trend. The results of Mann-Kendall test show that the temperature of Kerman and Anaar stations has a positive trend, but Shahrbabak station has a negative trend in August (summer) and November (autumn), Zarand and Sirjan stations have no trend. Rainfall in Zarand station has a positive trend in May (spring) and in other stations there is no trend and wind speed has a positive trend in all stations.

Extreme precipitation is one of the climatic risky behaviors that are associated with abnormalities and environmental-human consequences. This study has investigated daily rainfall  of 20 rain gauge and synoptic stations over 30 years (1987-2016) in the West of Gilan province, to determine the trend of extreme precipitation changes. In this regard, non-parametric Mann-Kendall test, Senchr('39')s Estimator slope, Poisson distribution, and IDW interpolation have been applied, respectively, to determine the existence of trend, significance, to determine the probability of rainfall occurrence   and to identify spatial patterns of precipitation occurrence with different probabilities. The results suggested an increasing trend in Astaneh-ye Ashrafiyeh, Bandar-e Anzali, Masuleh, and Astara and an extreme decreasing trend in Bash Mahalleh due to the Mann-Kendall test. Studying the significance or insignificance of changes trend by Sen indicated that this trend has been significant in Mashin khaneh, Bash Mahalleh, and Punel Stations; and the null hypothesis, that is, the insignificance of change, was rejected. Senchr('39')s Method revealed that there were no significant changes in other stations, and their randomization will be confirmed. To this end, the spatial probability distribution of  to  indicate kernel probability displacement for different x.  The maximum probability to various occurrences has been at Masuleh station and Poisson distribution is a proper assessment of precipitation in this region.

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.

One of the environmental crises that have caused a lot of concern in recent years is the pollution caused by wind erosion in arid and semi-arid regions, especially in Iran. Recently, it has been reported that about 26% of changes in atmospheric dust concentrations occurred due to changes in the drought index resulting from changes in precipitation to evapotranspiration. Increasing air pollutants concentrations, especially dust particles, had negative effects on agricultural production, human health, and the environment. Therefore, temporal and spatial analysis and continuous monitoring of these events in different regions, especially in arid and semi-arid regions, are of great importance. Accordingly, the main purpose of this study is to analyze the trend of dust pollution caused by wind erosion at different time scales and to investigate the spatial distribution of dust particles in Fars province, southwestern Iran, during the years 2000 to 2018.

In this study, using the pollution of dust storm index (PDSI), the pollution caused by wind erosion events in eleven synoptic stations located in Fars province was calculated. The frequency of local, moderate, and severe dust events was used to calculate this index. Then, the Mann-Kendall test was used to analyze the trend of monthly, seasonal, and annual changes. The trend of changes was calculated separately for the study stations. Furthermore, the map of spatial changes of air pollution in Fars province from 2000 to 2018 was prepared using the reverse distance weighting method. Finally, areas more sensitive to wind erosion were identified based on the generated maps using this method.

 Results :

Analyzing the trend of monthly changes in PDSI using the Mann-Kendall test showed that the most incremental and significant changes in dust pollution occurred in April, May, and February in Fasa, Shiraz, Dorodzan, and Zarghan stations. Meanwhile, the trend of decreasing and significant changes in PDSI has occurred mainly in Lar and Darab stations and from May to October. The results of the seasonal change trend showed that regardless of the confidence level, more than 70% of the study stations have experienced an upward trend in spring, summer, and autumn. In winter, all stations except Darab station have experienced increasing changes in air pollution. On an annual scale, the trend of decreasing changes was observed only in Darab and Lar stations, while the trend of changes in other stations of Fars province was increasing. The pattern of the spatial distribution of dust particles in Fars province showed that in 2003 and 2005, more than two-thirds of Fars province and mainly the central to southeast areas were faced with high dust concentrations. In recent years, and especially in 2017 and 2018, the distribution of dust particles has changed. In recent years, residents of the central to southwestern Fars province have suffered more from reduced air quality due to increased concentrations of atmospheric dust particles.

The growing trend of dust pollution caused by wind erosion events in recent decades has raised major concerns at various regional, national and global levels. Therefore, it is necessary to understand the trend of temporal and spatial changes of pollution caused by these events to reduce their adverse consequences in different regions. Based on the findings of this study, the trend of temporal changes in dust events and the pattern of dust particle distribution in the southern half of Fars province is also worrying because, in most cities of Fars province, an increasing trend in air pollution was observed. In addition, according to PDSI maps, a large part of the province is exposed to the dangers of dust storms and air pollution. Considering that PDSI is calculated based on the frequency of local to severe events, it can be concluded that the frequency of wind erosion events has increased in most cities of Fars province. In other words, these findings indicate the intensification of dust events and pollution caused by it in this province. Our results also showed that in the long-term (2000-2018), the southern half of Fars province, compared to the northern half, was more sensitive to dust events and, as a result, played a major role in dust production across the province. One of the reasons is drying the bed of Bakhtegan-Tashk, Maharloo, and Parishan wetlands, located in the southern half of the province, and have acted as dust generating sources, especially in recent years. As a whole, the results of this study can help managers and planners to prioritize managerial and executive measures to combat the risk of desertification and reduce the adverse impacts of dust storms in dusty areas.

Climate change and global warming are occurring as the most important environmental problem. It is necessary to study the trend of meteorological variables in order to detect climate change in each region. In this study, the trends of variables related to temperature (minimum, absolute minimum, maximum, absolute maximum and average) and precipitation (total precipitation, frequency of days with precipitation and maximum daily precipitation) in the annual time scale were investigated. Trend analysis was performed using non-parametric Mann-Kendall and Sen's slope estimator in 15 synoptic stations of Hormozgan, Bushehr and Sistan and Baluchestan provinces, which had complete data in the period of 1987-2019. Then, zoning maps of climate variables trends were prepared in Arc GIS software. The results showed that 3 temperature variables including: minimum, maximum and average had a significant upward trend in most of the area. The frequency of occurrence of significant upward trend related to temperature variables for each station showed that the stations of Bandar Abbas, Kish Island, Zahedan, Zabol and Iranshahr had a significant upward trend in 4 of the 5 temperature trends studied. Total rainfall in the region showed no significant trend, maximum 24-hour rainfall had a significant increasing trend only in Bushehr-Coastal Station and the frequency of days with rainfall in Bushehr-coastal had a significant decreasing trend. The results of the Sen's slope estimator showed that during 33 years, the highest rate of change of temperature variables, related to the absolute minimum, was 3.59 ° C in Kish Island. The maximum rainfall in Bushehr-coastal increased by 16.5 mm and the frequency of days with rainfall decreased by 11 days.

The aim of this study was to identify the temporal-spatial variations of temperature series in the eastern basin of Iran. Based on this attitude, the monthly statistics of average temperature, maximum temperature and minimum temperature of Sarakhs, Sahand, Birjand, Zabol, Zahedan and Saravan stations during the period of 1987-2019 were used. Data homogeneity was assessed by Chi-square test and data normality was assessed using Anderson-Darling test. For data with normal distribution, t-test and least squares method were used and for data with abnormal distribution, Mann-Kendall statistical-graphic test was used. The results showed that the average temperature in most months and most stations had an increasing trend. Mashhad, Birjand, Zabol and Zahedan have had an increasing trend in almost all months of the year. A decreasing trend was observed only in Zahedan station during December. The maximum temperature and especially the minimum temperature showed a lower trend and were out of trend in most months of the year. Time changes showed that the average temperature during the warm months of the year showed an increasing trend in more stations and in the cold months of the year less stations showed a trend. Of course, except for Mashhad, which has been a trend in most months of the year.

Dust is referred to sediments of less than 100 microns in size which are transmitted as suspended particles. Dust storms are events which naturally occur in arid and semi-arid areas, especially in subtropical latitudes. One of the most known sources of dust is the west of Asia, including Arabian Peninsula, Syria, Iraq, and Iran, especially Khuzestan Province. The purpose of this study is to investigate the frequency and trend of dust phenomena on hourly, monthly, seasonal and annual scale between 1995 and 2015 in Khuzestan Province. The method in this study is based on statistical computation of dust parameters and also the trend analysis of data based on Mann-Kendall test and spatial distribution maps of dust phenomena. The results suggests that 78.57 percent of dust event are occurred between 9.30 am to 15.30 pm local time, concurrent with peak of sun radiation and earth surface warming, dryness of soil and local pressure difference. The hourly trend analysis is increasing and significant in all hours and the highest increase occurred at 9.30 pm to 12.30 pm.49 percent of dusty days occurred in June, July and May and also 73 percent of them are in spring and summer as following from temperature increase and water and soil resources drying in the province. The seasonal and annual spatial distribution of dust indicates that most of dusty days in all seasons are located in west of province which suggests dominance of external sources as the main source of dust and the importance of topography factor in this area.The Z value spatial analysis suggests high increase of dust event in recent 20 years in southeast, south and central areas of the province and also on last hours of day which demonstrator development of internal sources activities in increasing trend of dust event in recent decades.

Investigating the behavior of atmospheric circulation during different periods can broaden our knowledge of large-scale changes in the climate. Based on recent Intergovernmental Panel on Climate Change assessments, the increase in greenhouse gases and other human activities will lead to the warming of the troposphere, atmosphere temperature drop, thickening of tropopause, less atmospheric circulation activity in the tropics, migration of atmospheric disturbance from poles toward middle latitudes, increasing of precipitation in tropical areas, etc. Since the middle-level atmosphere has the greatest effect on the occurrence of atmospheric phenomena in the surface of the earth, many studies have investigated the temporal and spatial changes of this level across the world. Most of these studies confirm the changes in the geopotential height anomalies at 500 hPa in some areas and identify them useful in forecasting temperature and precipitation variables, as well as phenomena such as flood and frost.

This study explored changes at 500 hPa using daily data of the US National Center for Atmospheric Research for the period from 1972 to 2015. Using cluster analysis, the behavioral patterns at 500 hPa were analyzed for a 44-year period, and the Mann-Kendall graphical test was used to identify the trend of change and its significance.

The clustering results show two main long-term patterns in middle-level atmosphere. In the first group with more days, the domination of the Mediterranean high landing over a large part of the study area and the its penetration toward Iran is noteworthy, whereas in the second group with far less days, there is the dominance of the sub-tropical high with one of its bulges over a vast area of Iran, which leads to sustainability and hot air in the warm days of the year. The analysis of the trend of changes in the middle-level atmosphere height using the Mann-Kendall method indicates significant changes in the study area during the period; with the significant increase being recorded for the last decade (after 2000) during the annual period and in the summer months of July and August. These results also showed no significant trends in the autumn, especially in October and November, either individually or collectively.

One of the results of climate change is the change in atmospheric patterns such as sea level pressure and the height of different layers of the atmosphere. The results show that the middle-level atmosphere height, which is a key components in atmospheric disturbances and precipitation, or lack thereof, especially in regions such as Iran, has experienced increase in various periods and throughout the statistical period under study. This height increase can lead to a decrease in rainfall and an increase in the duration and severity of droughts in these areas. On the other hand, occurrence of extreme temperature and precipitation anomalies in these areas is another result of this height increase. A suitable solution for dealing with its adverse effects is the optimal management of water resources.

A better understanding of trends in reference crop evapotranspiration (ET0) is crucial, in scientific management of water resources, in arid and semiarid regions. According to the fifth assessment report of the Intergovernmental Panel on Climate Change (IPCC), the global warming trend, which is mainly caused by the increasing amount of greenhouse gas emissions, will be continued. Climate change is known as a global environmental challenge facing humanity with implications for food production, natural ecosystem, and fresh water supply. The expected climate change is thought to have a severe impact on different elements of natural systems such as agriculture, hydrology, and ecosystem. reference crop evapotranspiration is one of the main elements of hydrological cycle affected by climate change. reference crop evapotranspiration can be considered as a measure of atmospheric evaporative demand. It is independent of crop type, crop development, and management practices. It provides a measure of the integrated effect of several meteorological parameters such as radiation, wind speed, air temperature, and humidity. reference crop evapotranspiration variability in a single station is affected by these climatic parameters. Estimating reference crop evapotranspiration is one of the important steps for calculating crop water requirements that has a special economic importance in the rationalization of water consumption in the agricultural field under current and future climate conditions. Moreover, this parameter plays an important role in the energy balance of basin ecosystems. Several hydrological processes, such as soil moisture dynamics, groundwater recharge, and runoff generation affected by ET0 fluctuation. 

The data of the 18 synoptic stations located in the west and Northwest of Iran were obtained from the Islamic Republic of Iran Meteorological Organization (IRIMO). In this study, the stations which had at least 20 years of daily data (up to 2016) were chosen for analysis. The gathered data including the meteorological parameters namely maximum air temperature (Tmax), minimum air temperature (Tmin), mean air temperature (Tmean), wind speed in 10 m height (U), maximum relative humidity (RHmax), minimum relative humidity (RHmin), sunshine hours duration (n), and actual vapor pressure (ea). Each of the mentioned data was checked for quality, separately. These data were used to estimate the daily values of ET0 in selected stations using the FAO-56 PM method. The trends of ET0 were detected by using the Mann–Kendall test. The slopes of the trend lines were computed by using the Sen’s slope estimator. And, to investigate the spatial and temporal variability the IDW interpolation method was used

The results showed significant increasing as well as decreasing trends in the annual and monthly ET0. Although, the increasing trends in ET0 was more pronounced than the decreasing trends. In the monthly scale, during the warmer months of the year, the observed increasing trends were more than the decreasing trends of the ET0. In the annual scale, the stronger positive trend in ET0 magnitude was found at Kermanshah stations (Z=5.79), and the strongest negative trend was found at Khodabandeh station (Z=-1.78). Also, in the monthly scale and in the warm season, the strongest positive trend magnitude was found in August at Kermanshah station, (Z= 5.43), and the monthly strongest negative trend magnitude was found in August at Khodabandeh station, (Z=-3.47). In general, it is possible to conclude that, in the recent decades the required water of the plants is increased in the studied area.

Reference crop evapotranspiration is one of the main elements of hydrologic systems. Climate change in different parts of the Earth impacted natural systems in a different way. This study examined the trends of ET0 in 18 weather stations selected in west and northwest of Iran. The FAO-56 PM method used to calculate the ET0. The MK method was used to detect the trends in monthly and annual ET0 time series.The Sen’s estimator was used to estimate the magnitude of the trends. Results indicated that most of the monthly ET0 time series had upward trends. In annual time scale, Most of the stations showed increasing annual ET0 trends, which were significant at 10 percent level. Therefore, it can be concluded that in all water-related activities, especially in agriculture, fresh water should be used scientifically. Otherwise, all of the water-dependent activities might be adversely affected in future.

Water and food security are serious challenges in climate change studies. the purpose of this study is to investigate the effects of climate change on water requirements of apple during the growing season. For this purpose, the ECMWF database has been used for observation data of Semirom and Urmia stations during the 20-year period (1996-2001).To check this quantity in the next 20 years, the daily  Downscaling dynamic data of the CORDEX project with a precision of 44% * 44% for the output of the ICHEC-EC-EARTH model under the two lines of 4.5 and 8.5 (RCP) was used for the period (2017-2037). In order to reduce the errors in the model estimates, the post-processing action of the estimated events was fulfilled. Then, minimum temperature data, maximum temperature, relative humidity, wind speed and radiation, potential evapotranspiration have been calculated using Penman-Monteith FAO method, which is more accurate than other models, and using the non-parametric Man-Kendall test and the Sen’s Slope estimator nonparametric Method in the confidence range, 95% evapotranspiration was determined. In the end, the water requirement was also examined during the growing season of apples. The results showed that evapotranspiration in both stations is increasing during the growing season. The ETo increase in the growing season of the apple tree stations was predicted from the base period for the trajectory of 4.5 and 8.5 for the Semirom 4.14.7 and 7.99.7, respectively, and for Orumiye Station, 26.5 and 11.8, respectively, and however, this increasing process will raise the apple's need for water. The highest amount of evaporation and water requirement in the observed and estimated data has occurred in the bud break periods, growth fruits. At this stage, the lowest effective rainfall and the highest average temperature have occurred but generally, the percentage of upcoming changes of germination stage was more than other stages.

Dust is one of the common phenomena in arid and semi-arid regions and can have significant effects on the climatic conditions of an area. Therefore, the present study was conducted to investigate the dusts in Kohkiluyeh and Boyer Ahmad provinces. In this regard, codes 6, 7, 8, 9, 31, 32 and 35 of dusts were investigated at Yasouj, Dugonbadan, Thay, Dehdasht, Likak and Imamzadeh Jafar stations on daily, monthly and annual basis. At first, the frequency of daily, monthly and yearly codes was checked at all stations and their daily calendar was prepared. Then the zoning maps from all of the codes were mapped in the months of the year and finally, the number of days with dust was investigated at Yasouj and Dogonbodan stations. The results showed that Dogonbadan Station with the frequency of 2381 had the highest dust incidence during the statistical period. The review of codes indicates that the two codes 6 and 7 were the most frequent at all stations. Code 6 at Dogonbadan, Likak, Imamzadeh Jafar and Thirud stations in 2012 was at Yasouj Station in 2009 and at Dehdasht station in 2008, with the highest frequency. Code 7 was also reported at Dogonbadan Station in 1992 and at Yasouj Station in 1371. The process of dusts at Yasouj and Dogonbadan stations also indicate that both cold-run stations in the year have had a drought-reducing process and the warm months have not been trendy. Both stations showed an increasing trend on an annual basis