نشریه پژوهش های اقلیم شناسی
پیاپی 54 (تابستان 1402)

The purpose of this research is to determine the best deployment position and stretching pattern of the side-to-side jet to create tarsal in the southwest of Iran, as well as to select the most frequent synoptic pattern in this region.

The daily rainfall data of stations in the southwest of Iran (Khuzestan, Chaharmahal, Bakhtiari, Kohgiluyeh, and Boyer Ahmad) during the statistical period in three solar cycles (1986-1997), (1997-2008) and (2008-2019) were received from the National Meteorological Organization. Orbital and meridional wind component data, geopotential height at 250 and 300 hPa levels, slp, specific humidity and omega from the US National Center for Oceanography and Environment (NCEP/NCAR) with a spatial resolution of 2.5 × 2.5 degrees. received. Then, using factor analysis and visual inspection, the most frequent patterns were determined for all three solar cycles.

The examination of the maps of the lower, border and middle level of the troposphere showed that in the severe droughts of southwest Iran, the establishment of high pressure Arabia over the Arabian and Oman seas and the movement of moisture from these seas to the low-pressure eastern slope of Sudan and the formation of a deep trough in the west of Iran from Europe to southern Sudan and Cold subpolar advection on the western low pressure slope of Sudan is the most suitable pattern for heavy rains and its continuation for several days in the southwest of Iran. The best location of the subtropical jet to strengthen the rain systems is the area between Egypt and the western coast of the Persian Gulf in southern Iraq, if the core of the jet is located in northwestern Saudi Arabia. And the main source of system moisture in all precipitation samples is the Arabian, Oman and Mediterranean seas.

Identifying the patterns of the teleconnection and analyzing their effects on the dynamic components and circulation patterns of the atmosphere can be useful for better understanding and knowledge of climate systems and consequently their prediction (Mueller and Ambrizi, 2007). The Arctic Oscillation (AO) and the East Atlantic–West Russia teleconnection (EA–WR)are among the most important teleconnection in the Northern Hemisphere. The Arctic Oscillation is actually the anomaly of atmospheric pressure at the sea level in the north polar latitudes (55°N) and middle latitudes (45°N latitude), which was first discovered by two scientists named Thomson and Wallace in 1998 It was proposed as the main reason for the variability of the Subtropical regions of the Northern Hemisphere. In the positive phase of this index, the polar convection is stronger than normal and the jet at the top of the atmosphere is strengthened and moves in the form of a ring of strong westerly winds from around the North Pole, and this causes colder air to be limited in the polar regions. As a result, in this phase, the western winds are strengthened in the North Atlantic area and create warmer and more humid conditions than usual in Northern Europe. In the negative phase, the polar vortex ring and the upper level jet of the atmosphere take a meridional pattern and the western winds move towards lower latitudes (middle latitudes). Also, in this phase, the western winds are weakened in the northern part of the Atlantic and can penetrate to the areas located at low latitudes including southern Europe, the Mediterranean and the Middle East.East Atlantic-West Russia teleconnection EA-WR is obtained from the standardized pressure difference or geopotential height of East Atlantic Ocean from West Russia.This teleconnection was presented for the first time by Branston and Livesey (1987) using the method of principal components analysis in the form of a pattern of monthly changes in geopotential height of 700 hectopascals. This pattern includes four main centers of negative geopotential height anomaly along the orbits from the Atlantic Ocean to China. In the negative phase, this is reversed. In the negative (positive) phase, climate conditions are often drier (more humid) than the average situation over a large part of the Mediterranean region (Krichak et al., 2002).

To investigate the mechanism of the Arctic Oscillation (AO) and the East Atlantic/West Russia Oscillation (EA-WR) in relation to the atmospheric circulation of the Middle East and Iran in two seasons: autumn (September, October, November) and winter (December, January, February), National Center for Environmental Prediction/Atmospheric Sciences (NCEP/NCAR) gridded data were used. The reason for using data with a spatial resolution of 2.5*2.5 degrees is that they are suitable for studying low-frequency phenomena on a planetary scale (Mohab al-Hajjah et al., 2015). Based on the purpose of the research, the data of geopotential height, sea level pressure, orbital component of wind and amount of precipitation for two seasons of winter (December, January, February) and autumn (September, October, November) were obtained between 1948-2020. Due to the importance of the level conditions of 200 and 500 hectopascals on the dynamic components of lower levels (Standel et al., 2021), these atmospheric levels were selected for investigation and analysis. After receiving the mentioned data and extracting the time series of these data, the map of the desired dynamic components was drawn and analyzed.Then the correlation maps between the mentioned teleconnection with parameters of geopotential height of 500 hectopascals, orbital wind component of 200 hectopascals, sea level pressure and precipitation amount In order to determine the long-term relationship of these links with the dynamic components - synoptic and precipitation of the region in the cold period of the year, it was drawn.

The pattern of correlation values between the meridinal wind speed level of 200 hPa and the AO teleconnection in the autumn season showed that a Rayleigh-shaped positive correlation line was drawn in the direction of the meridinals from the United States of America, the Atlantic Ocean, North Africa to the east of Iran.Both teleconnection have a strong positive correlation with the meridinal wind speed of 200 hectopascals in autumn and winter, Which means that, with the increase in the value of each of them in the autumn season, along with the increase in the meridinal wind speed, the tropical jet stream first has an meridinal - wave pattern in the direction of the Atlantic Ocean, north and East Africa, the Red Sea, and then it is formed by changing the shape with a meridian pattern from Iran to the west of Russia. Almost along the same path, there is a negative correlation between the mentioned teleconnections and the geopotential height of the middle level of the atmosphere in the two seasons of autumn and winter. By increasing the value of each of the mentioned links, the value of the geopotential height of the middle level decreases from the northwest side of Iran to the north of the Red Sea and the east of the Mediterranean, which indicates the penetration of cold polar air through the west of Russia to the areas located throughout the western half. and the northwest of Iran.

The results showed that the fluctuations of both teleconnections have a significant effect on the climate of the Middle East, especially Iran. In autumn and winter season, there is a positive correlation between the above-mentioned teleconnections with the meridinal wind speed of 200 hectopascals and a negative correlation with the geopotential height of the middle atmosphere in Iran and the Middle East. Therefore, the increase in the value of each of these teleconnections is associated with an increase in the meridinal wind speed at the upper level of the atmosphere and a decrease in the geopotential height of the middle level of the atmosphere in autumn and winter seasons. The East Atlas-West Russia teleconnections affects a wider area of Iran in autumn and winter.

Climate change and global warming may have direct effects on climate extreme values and temporal as well as spatial variations of these events. Alterations in natural and human communities caused by meteorological extreme events are more significant than those caused by climatic averages. These extreme events widely draw public attention, and are particularly foregrounded by governments and academic communities (An et al. 2019). Given the noticeable consequences of climate extremes, the Intergovernmental Panel on Climate Change (IPCC) organized a team of experts to investigate the challenges caused by extreme events and measure extreme indices (Houghton et al. 2001, Peterson et al. 2002). This team suggested 27 indices to investigate and measure climate extremes. These indices have globally drawn the attention of atmospheric sciences researchers, and many studies have been conducted based on these indices to investigate both past and future events. The literature review indicated that spatial and temporal variations of extreme climate events related to both the past and future have been sufficiently investigated by certain researchers abroad. However, extreme climate events in Iran have been rarely examined. The few studies to investigate the events related to temperature and precipitation extremes in the selected region using temperature and precipitation data and synoptic stations located in Western and Southwestern Iran.

The regions that have been investigated in the present study are Ilam, Lorestan, Khuzestan, Chaharmahal and Bakhtiari, Kohgiluyeh and Boyer-Ahmad, Bushehr, and Fars provinces in Western and Southwestern Iran. These provinces cover 28/9924 square kilometers comprising 17/6% of the whole country area. The data used in this study include average precipitation, and maximum as well as minimum daily temperatures at 28 synoptic stations located in Western and Southwestern Iran in a common statistical period of 30 years from 1988 to 2017. After selecting the stations, the Run Test was used for all the stations and precipitation parameters, and minimum were measured. Subsequently, a matrix of the daily precipitation data and minimum. as well as maximum daily temperatures for was prepared. Finally, extreme indices (26 precipitation and temperature indices as suggested by the expert group CCL/CLIVAR) were measured using programming in the context of the MMATLAB software environment, and the variation process in every index was examined using the Mann-Kendall test. Then, the required maps and diagrams were prepared.

The investigation of temporal variations in the occurrence of warm indices from 1988 to 2017 in Western and Southwestern Iran using the Mann-Kendall test (with a reliability level of 95%) indicated that the total trend of warm indices such as warm nights, warm days, the number of summer days, and the number of tropical nights for most of the stations has been increasing. However, the examination of temporal variations in the occurrence of cold indices using the Mann-Kendall test (with the reliability level of 95%) showed that the total trend of cold indices such as cold days, cold nights, and the number of frost days was declining.The significant finding revealed by the general investigation of the total warm and cold extreme indices in the regions covered in the present study is the prevalence of the warming trend over the examined statistical era. The results of the maximum of one-day precipitation amount and the maximum of five-day precipitation amount indices were also indicative of remarkable precipitation rates in the regions based on these indices. The average was 177 mm (in Kuhrang station). The average was 347 mm (in Kuhrang station). The trend of temporal variations in these two indices was also insignificant in the majority of stations in the regions corresponding to the R99p, R95p, R20mm, PRCPTOT, and CWD indices.

The investigation and analysis of the extreme indices trend revealed that the occurrence of warm extreme events was increasing, while the occurrence of cold extreme events was decreasing in the areas covered in this study. One of the main reasons behind these phenomena has been progressive global warming, particularly since the late 1990s. The results of the present study concerning temperature extreme events confirm previous findings (by Zhang et al. 2005, Alexander et al. 2006, Zhao et al. 2012, Varshavian et al. 2011, Miri and Rahimi 2015, Karimi et al. 2018) stated in some studies that investigated temperature extreme indices. The above-mentioned researchers have also highlighted the increasing trend of warm extreme indices and the declining trend of cold extreme indices in their studies. According to the results obtained by the investigation of the frequency of the occurrence and trend of extreme precipitation indices in the areas covered in this study, it can be asserted that the total precipitation rate has been declining corresponding to the majority of Iranian provinces. However, maximum precipitation rates have been declining from 1988 to 2017 despite exhibiting noticeable extreme amounts. Hence, it could be stated that extreme precipitation events increase, whereas the duration of the wet season shortens. Moreover, the declining trend of the wet days' index and the increasing trend of successive dry days' index in Western and Southwestern Iran could be indicative of the gradual intensification of water scarcity. The results of the present study concerning precipitation extreme events largely confirm the findings reported in corresponding studies (such as Klein Tank et al. 2006, I'm et al. 2010, Jones et al. 2012, Koozegaran and Mousavi Baigi 2015) that emphasized the increased extreme precipitation rate and the decreased amount of total precipitation rate.

Among the many human and biophysical factors in fire, climate and weather are also the main drivers of fire initiation and spread. But the separation of atmospheric processes affecting fire complicates the possibility of fire modeling and makes its management difficult. Considering the importance of fire and its close relationship with weather conditions, it seems that a comprehensive analysis of the spatial distribution of fire points along with the wind in Rasht city has a suitable position for further study. Therefore, in this research, we will try to provide a correct analysis of the spatial pattern of fires in Rasht city. Also, by examining how the fire points are distributed in this city, it is possible to determine the high-risk areas in terms of the occurrence of fire events in order to perform a better management to deal with possible incidents and fire extinguishing during Foehn wind in this city.

In order to identify Foehn wind days in Rasht, the data of maximum temperature, relative humidity, wind speed and direction were used for 8 years (1392 to 1400). In this way, the Foehn wind days were divided into three groups of moderate, severe and very severe days based on the criteria of 1sd, 2sd and 3sd of the maximum daily temperature of the period compared to the maximum temperature of the Foehn day. Then, using the average nearest neighbor method (ANN) and Ripley's K function, the spatial pattern of fire points was determined for moderate, severe and very severe winds.

The results showed that out of 160 Foehn winds that occurred in this area, 72 were moderate, 59 were severe, and 29 were very severe. The results showed that 72, 59, and 29 of the 160 Foehn winds that occurred in this area were moderate, severe, and very severe, respectively. In total, 23.6, 6.9, 0, 0, 0, 0, 2.8, 1.4, 9.7, 13.9, 16.7, and 25% of 100% of Medium Foehn winds happened from April until March, respectively. Also, 11.9, 5.1, 0, 0, 0, 0, 1.7, 1.7, 13.6, 22, 16.9 and 27.1 percent of the total Severe Foehn winds, , 10.3, 0, 0, 0, 0, 0, 6.9, 0, 13.8, 34.5, 13.8 and 20.7 percent of the total very severe Foehn winds occurred from April to March, Respectively. In this regard, the relationship between the maximum daily temperature and the average maximum temperature of the period (40 years) is 0.608 and is a direct relationship and is significant at both α=0.05 and α=0.01 levels. This relationship between the daily maximum temperature and the minimum relative humidity that occurs at noon is negative, inverse and is -0.504, which indicates that the relative humidity of the air decreases during the occurrence of a Foehn wind days in this area. The results of the multivariate regression model to determine the effect of each of the climatic variables on the maximum daily temperature showed that the Adj.R2 value of this relationship is equal to 0.566. Considering the large value of F and the value of Sig=0.000<0.05, we conclude that the regression model is suitable and most of the changes in the dependent variable have been seen in the regression model. Also, the two variables of average maximum temperature of the period and minimum relative humidity have a relationship with the variable of maximum daily temperature, and the effect of the first is direct and the second is inverse. As a result, with the increase in temperature caused by the Foehn wind, the relative humidity decreases greatly. The two variables of wind direction and average wind speed do not have significant effects on the daily maximum temperature caused by the Foehn wind. The results of calculating the average index of the nearest neighbor indicate that all three types of random, cluster and scattered patterns can be seen in the fire points of medium, severe and very severe Foehn winds. But the pattern governing the distribution of all the fire points of the period is also cluster type. Also, the results of Ripley's K function showed that the K value observed in the 10 investigated steps is greater than the expected K value, and this confirms the clustering of fire points in Rasht city.

In this research, it was found that the pattern governing the spatial distribution of fire spots in Rasht city and its surroundings in the months of January, February, March, April, October, November and December is of all three types of random, cluster and scattered patterns. However, the frequency pattern of the entire distribution of fire points for medium, severe and very severe Foehn wind was obtained as a cluster type. In other words, the clustering of the total frequency distribution indicates that there are different fire hotspots in the city of Rasht and its surroundings, which can be identified as different clusters. This feature of fire points has a great impact on the construction of new fire stations and it can be used in locating new fire stations to speed up the arrival of firefighters to fire situations. Finally, it should be said that the spatio-temporal information about the Foehn winds can help to understand its various effects at the local, regional and global scale.

Climatic changes result in extremes of weather. Increase in temperature at global land surface leads to increase in frequency, duration, and intensity of heat waves, consequently imposing thermal stress on cultivation systems. Heat waves and the resulting thermal stress damage the produce during growth and consequently reduce its yield (Moore et al. 2021), posing potentially serious threats to food security in the future (Miralles et al. 2019). The importance of examination of the properties of heat waves and their effects on agriculture, therefore, has kindled the interest of many researchers in this subject. For instance, the effect of climatic changes on agricultural produce in India has been studied by Kumar and Gautam (2014) and Patel et al. (2019). The effect of heat waves on plant growth and yields of agricultural produce has also been the subject of numerous studies; for example Fontana et al (2015), Chakraborty et al. (2019), and Hatfield and Prueger (2015) have studied the effect of heat waves on wheat and corn growth and yield. Acknowledging the effect of heat waves on the flowering stage as critical, Gusso et al. (2014) reckoned that these waves could strengthen the drought and, as a result, damage the produce. Deryng et al. (2014) and Chung et al. (2014) used climatic change models to study properties and consequences of heat waves on agricultural produce in future decades. The issue of adaptation to the consequences of climatic changes such as heat waves is also an important issue in management of the effects of heat waves on agricultural produce, which has been studied by Wreford and Adger (2010) and Pathak et al. (2018). Considering the catastrophic damage to cotton fields of Isfahan County during the heat wave of July and August 2013, the aim of this study is to identify the statistical properties and synoptic patterns of this heat wave in order to prevent the damage and plan for adaptation to such hazards in the future.

In order to fulfill the objective of this study – to identify the heat wave of July and August 2013 – two definitions have been used. In the first definition, the maximum daily temperature in July and August in weather stations of Isfahan County (stations of Isfahan, East Isfahan, and Kabutar Abad) was compared with the long term mean of maximum daily temperature; also, the heat wave was identified with two days or more in a row the maximum daily temperature was higher than the long term mean of maximum daily temperature. In the second definition, since thermal stress in cotton occurred at 40 degrees Celsius, days with the temperature of maximum 40 degrees Celsius or more in weather stations of Isfahan County, which continued for two days or more, were considered as heat waves.In order to synoptically analyze the patterns that caused heat waves in July 2013 and to compare them with the long term mean, the data of mean sea level pressure, mean geopotential height of July 2013, and the long term mean of the above-mentioned data in July from 1991 to 2020 were retrieved from https://psl.noaa.gov; using these data, the maps of sea level pressure and geopotential height at the level of 500 hPa were drawn in grads software.

By comparing the maximum temperature at the time of occurrence of heat wave with the long term mean and by considering the temperature at which thermal stress in the plant took place, findings of the present study verify the occurrence of the heat wave in July and August 2013. Also, results indicate that the establishment of Saudi Arabia cyclone at ground level and Saudi Arabia anticyclone at 500 hPa level and the expansion of its tongue to the central parts of the country led to the spread of heat wave to the Isfahan County in July 2013. In this study, examination of maximum daily temperatures and comparing them with long term mean of daily maximum temperature indicated that in July and August 2013, the Isfahan County had 29 days with temperatures higher than the long term mean, from July 12st to August 9th. In fact, long-term duration was one of the important properties of the heat wave in July and August 2013. Even when considering 40 degrees Celsius for the occurrence of thermal stress in cotton, the long-term heat waves duration which last about 6 or 7 days also occurred in Isfahan in July and August 2013. According to the second finding of this study, the mean sea level pressure and 500 hPa pressure level patterns in July 2013 were not significantly different from the long term mean sea level pressure and 500 hPa pressure patterns in July from 1991 to 2020. However, the strengthening of the Saudi thermal low pressure pattern on the earth's surface and the strengthening of the Saudi Arabia high height at the level of 500 hPa compared to the long-term average, which causes more subsidence of the air and as a result the impossibility of movement and also warming of the air in the lower layer of the atmosphere, caused the entry of warm air from Saudi Arabia to the center of the country and it has been an effective pattern in creating a heat wave in Isfahan County.

This study demonstrates the properties of the heat wave of July and August 2013 in Isfahan County, including the difference in temperature, compared to the long term mean temperature, daily and hourly duration, and synoptic patterns that contributed to the formation of the aforementioned heat wave. Considering the detrimental consequences of heat waves, especially in the agricultural sector, precise identification of the heat wave which damages the produce is necessary in order to plan for adaptation to the conditions resulting from heat wave, and for crisis management in order to reduce the damage to the produce in the future.

Investigating of extreme temperature changes due to Global Warming, drought and the occurrence of cold and frost is very important. Therefore, in this research, the trend and projection of changes in temperature extremes in northwest Iran in the base period (1985-2014) and three periods of the near future (2021-2050), the medium future (2051-2080) and the far future (2081- 2100) was paid. For this purpose, two extreme temperature indices including frost days (FD) and ice days (ID) and the Maan-Kendall trend test were used to check the changes. In order to anticipate the changes in the future period, the best model after evaluating 7 General circulation models (GCMs) from the Coupled Model Intercomparison Project phase 6 (CMIP6) under three The Shared Socioeconomic Pathway including SSP1-2.6, SSP3-7.0 and SSP5- 8.5 was used. Spatial distribution of the trend of changes in extreme temperature in the base period showed that by moving from north to south and from west to east, the ice days increase. The core of the maximum ice days has also been studied almost in the south of the region. According to the results, the average frost days and ice days in the base period are 101 and 19 days per year, respectively, and the maximum and minimum frost days are 146 and 52 days, respectively, for Sarab and Parsabad stations, and the maximum and minimum frost days are also, with 42.32 and 1.23 days, it is related to Zarineh and Parsabad stations. Also, the trend of changes in frost days and ice days in the base period in most stations is a decrease, which is significant at the 0.05 level. The evaluation of different models with different error measurement indices showed that MRI-ESM2-0 and MPI-ESM1-2-L models have the best performance in simulating extreme temperature in the study area. The evaluation of the trend of changes in frozen days and ice days using the Mann-Kendall test in the basic period showed that the trend of changes in most stations is significant at the 1% level. The distribution of changes in the future period also showed that the trends are similar to the base period, so that the decreasing trends in the studied indicators will intensify in each period, especially based on the SSP5-8.5 scenario. Thus, at the end of the 21st century, frost days and ice days have decreased by 45 and 13 days, respectively, and the largest decrease is related to the cold stations of the region, which shows that with the increase in temperature, the index Frosts and icy days will decrease.

Drought is a complicated natural phenomenon that occurs basically due to the lack of precipitation over a time period. And its occurrence usually results in great costs on various parts of the natural and the society. Among the various indices in climate drought monitoring, the SPI index (McKee et al., 1993) is the most well-known index, in terms of easy access to its data (rainfall); It is also possible to calculate it in any time window; Ability to calculate magnitude, frequency and continuity; The possibility of quick detection of soil moisture and the possibility of showing the spatial distribution of drought-dominated areas are widely used all over the world (Mishra and Desai, 2005). Standardized Precipitation Index (SPI) can be calculated for any location based on long-term recorded precipitation data. Calculating the SPI drought index in each of the time scales can be considered as one of the advantages of this index. The length of the rainfall data recording period as well as the nature of the probability distributions play an important role in calculating the SPI drought index and these factors are among its limitations.

Methods and materials:

In the present research, the uncertainty of SPI estimation in choosing the length of the statistical period and time scale was investigated using monthly rainfall based on the gamma distribution function at Bandar Abbas synoptic station in two periods of 31 and 64 years. Therefore, the rainfall for the time scales of 3, 6, 12, 24 and 48 months in the two mentioned time periods was calculated and then using the bootstrap method for each rainfall event in each time scale, 1000 random data were generated and the SPI confidence interval was about 95% confidence was calculated. The size of the confidence interval (the difference between the upper band and the lower band) was considered as uncertainty and the absolute ratio error (ARE) between the estimated and observed values was calculated.

ARE and uncertainty due to bootstrap estimation were estimated in two time periods and scales from 3 to 48. The greater the difference between the bands, the lower the certainty and the greater the uncertainty (Vergeni et al., 2015). Therefore, a longer period of time (large number of samplings) has less uncertainty, since the number of samples decreases as the time scale increases, so the uncertainty bandwidth increases. For example, in the 3 and 6-month scale in the 31-year period, the estimation error is 0.09, 0.11 and in the 66-year period is 0.03, 0.05, and the uncertainty has decreased from 0.051, 0.63 and 0.38, 0.41, respectively. In the 12-month scale, the error rate in the short and long term is 0.12 and 0.01, respectively, and the uncertainty is 0.81 and 0.55, respectively. In the 24-month scale, the error in the 31-year period is 0.31, which decreases to 0.1 in the long-term period of 66 years, and in 48 months, it decreases from 0.45 to 0.27, and in the same way, the uncertainty level in the long-term period is Scales 24 and 48 are reduced.Based on the results of two short (31 years) and long (66 years) samples, it showed that there was more uncertainty and error in the samples with a small number, and considering the overestimation or underestimation caused by the length of the short period in the diagnosis of drought classes Historical events have been misjudged and lead to inappropriate drought mitigation measures, as classifying a high-grade drought event (Class 9) to a lower grade (Class 8 or lower) can lead to misleading decision-making.

SPI was able to successfully detect historical droughts in the two investigated periods. The increase of records from 31 to 66 years led to the emergence of one of the most unique features of SPI, i.e. repeatability, reversibility and predictability. The confidence interval resulting from the difference between the upper and lower bands estimated by the bootstrap resampling method indicates uncertainty, the smaller the bandwidth or the result of the difference, the lower the uncertainty and the more reliable it is. In this research, the error caused by bootstrap estimation in 1000 sampling times was also estimated. Based on the obtained results, increasing the number of samples from 31 years to 66 years causes a decrease in uncertainty and error, and as a result, increasing the time scale due to the decrease in the number of samples due to data averaging causes an increase in uncertainty and estimation error. The studied area has It has had long dry and wetter periods in the past and has experienced numerous historical events. Therefore, it is necessary to pay attention to the possible judgments caused by wrong estimation and uncertainty in the observational data, and in this way, seek to reduce the possible damages caused by overestimating or underestimating drought.

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.

Identifying the teleconnection patterns and analyzing their effects on the horizontal structure of circulation patterns can be useful for better recognition and understanding of anomalous climatic events. Temperature, precipitation, and wind, which are the main factors in weather and climatology classifications, are among the parameters whose abnormal increase or decrease can cause irreparable harm and damage to humans, and predicting the abnormalities of these factors can be useful. The teleconnection is as the name suggests; In fact, it deals with the relationship of different climatic parameters in different parts of the world. A significant part of the damages caused by climatic hazards is related to hot and cold waves, destructive floods and violent storms. The term teleconnection is often used in atmospheric science to describe climate links between geographically separated regions. Climatic signals that express changes in temperature and air pressure in the oceans are considered one of the most influential parameters on a global scale on weather patterns, especially precipitation, considering the effect of large-scale climatic factors on extreme events, by examining the effect of these signals on the accuracy of monitoring and forecasting. Floods increase. Atmospheric circulations are very variable. In general, the occurrence of extreme atmospheric-climatic phenomena such as heavy rains and sudden changes have the largest scope of damage to water resources, agriculture and even people's daily life. Having the necessary knowledge of the extent of these phenomena, changes and their prediction will be of great help for more accurate planning in different watersheds, which will reduce the negative effects caused by the occurrence of these phenomena and benefit from their positive effects. These changes lead to the emergence of weather patterns and forms of atmospheric currents that occur on different time scales. teleconnection patterns represent large-scale changes that occur in the pattern of atmospheric waves and rivers and affect the pattern of temperature, precipitation, the path of showers and especially the performance of remote climates in vast territories. During the El Nino-Frein event, the positive sea surface temperature anomalies are more intense in the tropical eastern Pacific Ocean, which causes a significant reduction in the sea surface temperature gradient and, as a result, the weakening of the easterly winds between the tropical eastern and western Pacific Ocean. The purpose of this research is to investigate the relationship between temperature, precipitation and wind anomalies in Mazandaran with Teleconnection indicators. For this purpose, the data of 4 stations of Ramsar, Nowshahr, Babolsar and Qarakhil Qaimshahr were used in the period of 1984-2020. Teleconnection indicators data were obtained from the National Oceanic and Atmospheric Administration (NOAA).

Using the multivariate regression method, the relationships between Teleconnection indices and weather parameter anomalies were investigated. The method used is the backward type, in which all predictor variables that were selected according to the highest correlation coefficient are first entered into the equation and those with lower confidence coefficients are removed one by one from the model. In this research, four-time steps were used: monthly, simultaneous, one month ahead, two months ahead and three months ahead. In most of the indices, which are less related to the surface temperature of the oceans and are subject to pressure changes, the correlation coefficient was often accompanied by a decrease with the increase of the time period. For each month, temperature, precipitation and wind anomalies were extracted in two stages, first by using the (Z) value greater than 0.5 and less than -0.5, and then by applying the 90th and 10th percentile methods. The efficiency of the relationships obtained was calculated through RMSE.

The lowest RMSE with a value of 0.81 and a standard error of 0.85 is specific to the wind parameter in the time step of the same month and from the first method (0.5<Z<-0.5) whose changes have a negative relationship with the CAR index (Caribbean SST Index) and a positive relationship with the indices It has SOI (Southern Oscillation Index), AMO (Atlantic multidecadal Oscillation) and PWP (Warm Pool Pacific). The average correlation coefficients of different time steps for the output data of the first method (moderate to very severe anomaly) are 0.72 for wind, temperature 0.57 and precipitation 0.49 and in the second method (very severe anomaly) for precipitation 0.97, wind 0.86 and temperature 0.68.

AMO, GLBT.s (Global Mean Lan/Ocean Temperature) and SOI indices are the most important oceanic indices of this research in the cold season of Mazandaran. According to the observed changes, there is a significant relationship between the periodic phase change of the AMO index and the Mazandaran wind parameter; So, the correlation coefficient between these two is 0.7.Keywords: Multivariate regression, Teleconnection, anomaly, temperature, precipitation, wind, Mazandaran

Synoptic systems have a major role in the earth’s climatic changes. These systems, especially cyclones and anti-cyclones, move to transport air currents, and thus, sensible and latent energy, thus alternatively causing instability and stability in one region. Cyclones are synoptic systems in which sea level pressure is low, the air current is ascending, and the wind direction in the northern hemisphere is anti-clockwise. The vertical air movements in cyclones create clouds, precipitation, and even thunderstorms. Considering the literature on the relationship between heavy precipitation and cyclones, the frequency, temporal and spatial distribution and main paths covered by them have been examined; however, it is thus noted that few studies have ever investigated the three-dimensional structure of cyclones and their structural changes during the distance covered. For this, this study aimed to examine the three-dimensional structure of Mediterranean cyclones entering Western and Northwestern Iran through an immediate set of atmospheric variables.

This study used two different databases to identify Mediterranean cyclones entering Western and Northwestern Iran in the cold spells of the year (October-May). The first database pertains to the daily precipitation data of 15 synoptic stations of Western and Northwestern Iran for 10 years (from 2004 to 2013), obtained from Iran’s Meteorological Organization. The second database also pertained to the variables of atmospheric temperature, specific humidity, geo-potential height, sea-level pressure, vorticity, wind meridional component, and wind zonal component, all of which were derived from the European Center for Medium-Range Weather Predictions website (https://www.ecmwf.int) in the form of daily observations for 10 years (from 2004 to 2013) for the cold spells of the year (October -May).After data were obtained, the following five-step algorithm was defined to investigate the three-dimensional structure of cyclones entering Western and Northwestern Iran with origin in the Mediterranean Sea.Step 1: Selecting the most pervasive precipitation days in Western and Northwestern Iran=Step 2: Detecting the time and place of formation of Mediterranean cyclones at 1000 Hpa levels Step 3: Tracking cyclones at 1000 Hpa levels during the cyclone lifespan Step 4: Identifying cyclones at various pressure levels and their bonding together Step 5: Investigating the three-dimensional changes of cyclones during their lifespan

The main goal of this study was to understand the three-dimensional structure of cyclones entering Western and Northwestern Iran with origin in the Mediterranean Sea. For this aim, and to determine Mediterranean cyclones and locate their formation in the Mediterranean Sea, a five-step process was introduced. According to this process, 93 cyclones causing pervasive precipitation in Western and Northwestern Iran in 10 years (from 2004 to 2013) were identified and their three-dimensional structure was determined. The most important results from investigating the three-dimensional structure of the cyclones were as follow:• Most cyclones causing pervasive precipitation in Western and Northwestern Iran had initially shallow and middle depths then developed into deep cyclones during their paths. Before their central cores were established on land, most cyclones caused pervasive precipitation in Western and Northwestern Iran.Except for the beginning days of the birth of cyclones causing pervasive precipitation in Western and Northwestern Iran, vorticity values, being negative at some levels and positive at some other levels, revealed at all levels positive values during [cyclones’] course of movement eastwards in the remaining days. On days with pervasive precipitation in Western and Northwestern Iran, vorticity in cyclonic centers increased, especially at upper atmospheric levels.When shallow cyclones are formed on European land, there is always a kind of weak temporal inversion at lower levels of the atmosphere, which can be a major orographic feature of cyclones. In the course of the Mediterranean cyclones’ movement eastwards, the temperature gradient in the central core of the cyclones involves many changes. When cyclone centers are established over the seas, the temperature gradient is low, and when established on land, it is high.The daily changes of cyclones’ central cores during their course of movement eastwards are low at the seas and high on land. Wind zonal component values in the center of cyclones causing pervasive precipitation in the west and northwest of Iran were greater than those of wind meridional components.

An investigation of the most important changes of atmospheric variables (e.g., geopotential height, vorticity, temperature, humidity, and wind meridional and zonal components) in two horizontal and vertical dimensions during the life span of cyclones causing pervasive precipitation in Western and Northwestern Iran determined that thickness (vertical spreading), vorticity, temperature, humidity, and wind zonal and meridional components underwent large scale changes. The thickness of cyclones during their life span saw an increase, with some shallow cyclones changing into deep cyclones. Vorticity also saw positive values at all levels on all days, except for the beginning days when it held negative values at some levels, and positive values at some levels. Also, the temperature gradient in the central cyclonic cores saw changes. When deployed on the seas, cyclone cores had a low-temperature gradient, and when placed on land, they had a high-temperature gradient. During the cyclone’s life span, the specific humidity value by the time of pervasive precipitation in Western and Northwestern Iran increased at all levels, with the wind zonal component value being greater than the wind meridional component value at most levels.

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.

The rapid growth of industrial activities and as a result the increase of greenhouse gases in the last few decades has caused the disturbance of the global climate balance, which is referred to as the phenomenon of climate change. The negative effects of this phenomenon may intensify in the future due to society's attitude towards the rapid development of industry and less attention to the environment. There is a lot of evidence that these changes are happening; Adapting to climate change includes a set of management measures to reduce harmful consequences and benefit from it. Mitigating measures include reducing greenhouse gas emissions, promoting and expanding clean technologies, and protecting forests to deal with climate change; these are necessary even though these actions will slow down the occurrence of climate change, they are not able to halve or reverse the process of this phenomenon in the future. Therefore, in the medium term, society needs a specific strategy to adapt to the expected changes. Adapting to climate change is based on a better and more appropriate understanding of the effects of climate change and making informed decisions in taking measures to deal with this phenomenon. Adaptive strategies with the effects of climate change include a wide range, some of which are non-engineering or non-structural (education and insurance) and some are engineering or structural (such as structural measures and changes in management style).Insurance is one of the main methods of non-structural adaptation, and in a situation where this trend is increasing due to the growing trend of the harmful effects of greenhouse gases and the intensification of the effects of climate change, paying attention to the experiences of developed countries and adapting to the existing conditions of the country in line with the attention It is very important to have insurance products compatible with climate change that are also compatible with the country.

The research method considered in this article is based on the qualitative research method, and first, scientific reports and related sources were extracted, and the experiences of countries were extracted by examining written documents and using a comparative approach. To present the results, the extracted outputs were analyzed into three main classes of general understanding of the effects of climate change, insurance, and product development. The United Nations Development Program (2021) includes an index called HDI to determine the development of countries. This index is determined based on education, health, lifestyle, etc. The numerical value of this index varies between zero and one, and for developed countries, a value higher than 0.8 is considered. In this article, the value of this index based on the statistics of 2021 is the basis for the division of developed countries, and among the developed countries, Spain, Great Britain, Italy, Iceland, Belgium, Turkey, Romania, Sweden, Finland, Malaysia, New Zealand, Australia, Austria, Canada, France, Japan, Norway, Bulgaria, Germany, Denmark and the United States of America were considered as selected countries.

Climate change is one of the main challenges of the last century. With the formation of the Intergovernmental Panel on Climate Change at the international level, comprehensive policies in this field were taken into consideration and studies related to investigating the effects, relief, and adaptation to climate change were expanded. Structural and non-structural approaches are the two main approaches to adapting to climate change, and the current research is trying to use an adaptive approach, which is part of the non-structural strategy based on climate change risk management and centered on "insurance".The results showed that in general, the emission of more than half of the greenhouse gases in the world occurs in developed countries and their share of insured losses is higher, and also the governments in these countries seek to understand the general trend of the effects of climate change and respond to it. Therefore, examining the experiences of these countries in the field of providing solutions to face climate change is considered necessary and useful. These ongoing solutions include insurance plans and coverages, climate change risk management strategies in insurance, climate change risk transfer methods in insurance, and insurance products tailored to climate change.

The first step regarding the general understanding of the risk of climate change is to know the effects of climate change and especially the threats caused by climate change in the field of natural hazards and consequently the threat to the insurance industry. From this point of view, developed countries have experienced a favorable situation, which has become a platform for additional experiences in the field of insurance and product development in the face of climate change. Therefore, examining the experiences of these countries in the field of providing solutions to face climate change is considered necessary and useful. These ongoing solutions include insurance plans and coverages, climate change risk management strategies in insurance, climate change risk transfer methods in insurance, and insurance products tailored to climate change. Providing insurance products suitable for catastrophic events, including optional coverage especially for storms and floods, providing insurance for agricultural products or high-risk product insurance, comprehensive legal mandatory insurance against damages caused by natural hazards, creating a national solidarity fund with the aim of financial support for damage prevention. Providing insurance incentives for preventive measures, green loans for financial support of adaptation measures are among the most important and widely used plans and insurance products reviewed in selected developed countries.

Considering the phenomenon of climate change and subsequent changes in plant water requirements, it is crucial to recognize and estimate climate change in the coming decades with the aim of proper environmental planning to adapt to future climate conditions and reduce its effects. The main factor in the consumption of water resources in arid and semi-arid areas is agriculture and, accordingly, evaporation-transpiration, therefore, awareness of the process of changes and its prediction plays an effective role in planning, development, and water resources management. Since evaporation-transpiration accounts for an important part of the water balance of arid and semi-arid regions, its correct estimation is very important in the optimal preservation of water resources. On the other hand, knowledge of evaporation-transpiration process is necessary to estimate plant water consumption and design irrigation systems. According to the conducted research, estimation of evapotranspiration in the present and future periods is one of the basic needs of development managers, therefore, this research aims to evaluate the evapotranspiration potential in the base period (1991-2005), and predict temperature changes, using 3 scenarios (RCP2.6, RCP4.5, and RCP8.5) and evapotranspiration based on CMIP5 models (1.1 BCC-CSM and CCSM4) in the 75 year period (2025-2100) was carried out in Tabriz city.

For this purpose, the Penman-Monteith method was used as a standard algorithm to estimate potential evaporation and transpiration in the basic period (1991-2005). Then, potential evaporation and transpiration in the period of 2025 to 2100 were estimated using 2.6 RCP, 4.5 RCP, and 8.5 RCP scenarios and the LARS-WG6 model. Finally, the predicted values of evaporation and transpiration in future periods were predicted using the statistical indicators and the calculated evaporation and transpiration values for the base period (1991-2005). The ROC skill score curve also was used in order to general assessment of the quality of the estimations.

The results showed an increase in the predicted potential evaporation and transpiration under the RCP scenarios. In all three scenarios, the highest amount of evaporation-transpiration was obtained in July and the lowest amount was obtained in December. Moreover, an increase in the predicted transpiration evaporation was observed in July, August, January and February, compared to the base period. In addition, a decrease in the predicted transpiration evaporation was obtained in November and December, compared to the base period. In the RCP 8.5 scenario, the difference was much higher than in the base period. The evaluation of the model performance showed that for the hot months of the year, the model had a better ability to estimate the amount of potential evaporation-transpiration compared to the cold months, and the lowest RMSE error was in the hot months, so that in January with a value of 0.15 mm, the lowest value Dara showed the error. A comparison between the months indicated the two months of February and August as the best estimation for the estimation of annual evapotranspiration values. Likewise, the results showed that in all future periods and under all scenarios, the average reference evaporation and transpiration in annual scales will increase significantly at the level of 0.01 compared to the base period. The verification results also showed an acceptable ability for the predictions of the potential transpiration evaporation model.

This research amed at investigation of the amount of reference evapotranspiration changes based on RCP radiative forcing scenarios and climate models from 2025 to 2100 in Tabriz. The obtained results indicate the increase of reference evapotranspiration in all RCP scenarios for each of the future periods. In addition, the highest percentage of the reference evapotranspiration changes in the 8.5 RCP scenario is more than other scenarios because this scenario predicts the worst climate conditions and obvious changes in evapotranspiration will occur. The results of this research can be beneficial to solve the challenges of managers and relevant officials in the future periods. Considering this, the water, environment and health sector planners should adopt the necessary solutions for adaptation and reducing the consequences. Reasonable use of water resources is inevitable under the conditions of warming weather in Tabriz. Increasing evaporation and creating important changes in the quality and quantity of water resources, consequently changes in the quantity and quality of agricultural products. This situation determines the necessity of planning changes in the exploitation of water resources and agriculture. The future plans should be such that the upcoming changes have less harmful effects on the water and agriculture sector in this region. It is necessary to consider measures to improve the irrigation system, reduce evaporation, reuse wastewater and improve the cultivation pattern.

One of the most important and practical issues in today's world is weather forecasting. Forecasting the weather condition reduces the losses and damages of critical weather conditions. Weather forecasting can be effective in applications such as agriculture and air transportation. One of the methods that can be used to learn and predict the weather is deep learning networks, including convolutional neural networks. One of the important challenges of the convolutional neural network is that it performs feature selection unintelligent by using a number of convolution operations. In this article, a collective intelligence method is presented to improve the accuracy of forecasting weather conditions by convolutional neural network. The evaluations using the data sets related to weather conditions show that the proposed method, which has an accuracy and sensitivity of 96.32% and 96.14%, respectively, compared to the CNN deep learning network, has been able to achieve prediction accuracy of about increase by 8.35%.