climate change

Environmental problems in the world are a manifestation of unsustainable and inconsistent development with the capacities of the earth. Climate change is among all the problems, due to the global impact on the scale of the earth and effects such as floods, storms, unusual rain showers, increasing intensity, duration and volume of droughts, heat waves, melting of polar ice, rising sea water levels and going under water, loss of coastal lands, increase in minimum and maximum temperature in most areas, increase in evaporation and transpiration and water requirement of crops and Baghi, more evaporation of surface water and reduction of available fresh water sources, reduction of precipitation, increase of erosion and dust storms have attracted the attention of countries more than before. Iran, as one of the countries influencing the increase of greenhouse gases, is trying to increase adaptation and reduce the risk of climate change risks in order to manage surface and underground water resources, agriculture and improve the level of food security, natural resources and biodiversity (biological resources) and health of the country. In this regard, it is necessary to establish the governance of climate change in the policies and executive measures of the country at different national, regional, provincial and local levels in such a way that adaptation to it is implemented as a part of the country's daily life and development environment and as a result of increasing the level of environmental resilience, social, economic and cultural, all classes will benefit from its results. Climate change is one of the important factors that will affect different parts of human life on the planet and will have harmful effects on environmental, economic, social and especially water resources. For a long time, the change in meteorological characteristics of different regions of the world has been proven for researchers. The reduction of precipitation, reduction of surface currents and changes in the production and performance of agricultural products can be felt in many regions of the world. Our country is also facing many issues in this regard. Climate change has a significant impact on water resources and environment, which in turn is reflected in agriculture, society and economy.The increase in the concentration of greenhouse gases in the last few decades and the resulting increased temperature have led to significant changes in meteorological elements. Global warming, climate change and changes in temperature and precipitation parameters have now become one of the most important environmental challenges in the world. The reason for this is that these changes will cause droughts or severe, short and long term floods in the future. Therefore, one of the ways to reduce the effects of climate change is to evaluate its effects on rainfall and temperature in each region.

In order to simulate the climatic data, at first, the observational data of Arak synoptic station including minimum temperature, maximum temperature, precipitation and daily sunshine hours in the statistical period of 1980-2005 were obtained from the country's meteorological organization. Also, CanESM2 global model data under RCP2.6, RCP4.5 and RCP8.5 scenarios along with observational data related to National Center for Environmental Variables Prediction (NCEP) were downloaded from this center's website. In order to scale the output data of CanESM2 and HadGEM2-ES models, LARS-WG model was used. LARS-WG model is also one of the statistical exponential microscale models. This model is one of the most famous meteorological data generation models, which is used to generate daily data of maximum and minimum temperature, precipitation and sunny hours in a station under current and future climate conditions (Alizadeh et al., 2013). In this research, the 6th version of this model was used to scale the output of the HadGEM2-ES model. In the LARS-WG model, after receiving the daily observation data (minimum temperature, maximum temperature, precipitation and sunny hours), the statistical characteristics of the data were extracted. Then, in order to ensure the ability of the model, a series of artificial data was produced in the base period (1980-2005) and compared with the observational data. In order to calibrate and ensure the accuracy of LARS-WG model performance, simulated variables and real data were evaluated. The results show that the LARS-WG model has a good accuracy (R2=0.99) in simulating the minimum and maximum temperature. Also, the accuracy of the model in simulating precipitation (R2=0.98) is acceptable.

Based on the results of the model under the RCP8.5 scenario, the LARS-WG model shows a decrease in rainfall in all three periods, which is consistent with the assumption that the continuation of global warming will lead to a decrease in rainfall. Based on the results, LARS-WG model has predicted minimum temperature increase in all three scenarios and all three periods. Regarding the annual maximum temperature, the results of the LARS-WG model have increased in all three scenarios and all three periods compared to the base period. The minimum temperature and the maximum temperature simulated by the LARS-WG model increase under all three scenarios to reach the maximum value in the RCP8.5 scenario, which indicates the effect of the intensity of carbon dioxide emission concentration in the atmosphere as well as other It is a greenhouse gas. Also, the results showed that the most changes in the maximum temperature related to the RCP 8.5 scenario (from 23.12 in the first period to 26.51 degrees Celsius in the third period), the most changes in the minimum temperature related to the RCP 8.5 scenario (from 8.71 in the first period to 60/11 in the third period) and the most precipitation changes are related to the RCP 8.5 scenario. The period studied in this research was 2021-2040 (first period), 2041-2060 (second period) and 2061-2080 (third period). The modeling results show a decrease in rainfall in all three periods, which is consistent with the assumption that the continuation of global warming will lead to a decrease in rainfall. The minimum and maximum temperature changes showed that in most cases, the minimum and maximum temperature will increase in the future. The maximum temperature increase was more than the minimum temperature, so that the highest temperature increase occurs in the month of February by 1.89 degrees Celsius compared to the base period. Examining the changes in the amount of rainfall also showed that the lowest amount of rainfall in the coming period will be observed in the month of June in the amount of 07.07 mm. A decrease in rainfall on the one hand and an increase in temperature on the other hand can indicate that the increase in evaporation and transpiration and the decrease in snow cover can move the water balance towards land and reduce water reserves.

The impact of climate change and global warming on Earth's climate and other systems such as water sources, agriculture, environment, industry, health and the economy as a known the threats to sustainable development. So the effects of climate change on different systems and adaptive solutions to deal with the negative consequences of this phenomenon in future periods is essential. So according to importance of the issue, the purpose of this study was to evaluate the effects of climate change on temperature, precipitation, runoff and finally hydrological drought in the “Roude Zard” watershed in the future. For this purpose, data from the years 2000-1971 as a base data to small-scale model of LARS-WG introduction and calibration data for the years 1997-1990 and 1989-1974 years data were used to validate models of rainfall-runoff IHACRES. In order to evaluate hydrologic drought index SDI was used. Results show that increase in mean annual temperature in the study area 1.02 degrees Celsius as well as the expected changes in mean annual precipitation to the study area 11/91 percent and 73/78 millimeters. Results IHACRES model to simulate rainfall-runoff study area show that this model is suitable. The simulation results runoff also indicated an increase in the average runoff affected by climate change in some of the months of January, February and March and a decrease in average monthly runoff out of the area in September, October. Also results of the SDI index show increase in intensity of drought in the future compared to the base period. The results of this study will be to adapt to climate change studies in order to provide suitable management strategies used in the study area.

Small changes in temperature and rainfall regime or changes in the frequency and limit of climatic events can reduce the composition and distribution of plant species as well as their production. For the effective protection and management of natural ecosystems, it is necessary to identify the climatic factors affecting the distribution of plants in the present and use them to predict the distribution of habitats in the future. Climate change has an effect on the biological characteristics of species and therefore it is considered as a major concern for the management and protection of biodiversity. One of the important effects of climate change is to create changes in the distribution range of species. The studies conducted in the field of the effect of climate change on the distribution of plant species and communities show that in the 2030s and 2080s decreases to a large amount of domain the spread of all plant species and communities. he results of research on the effect of climate change based on species prediction models show that in the coming decades, due to the increase in temperature, they will migrate to higher altitudes and their area will decrease.
Predictive habitat models determine the suitability of the habitat for the establishment of plant species and help natural resource managers to identify factors that threaten the population of species, determine important factors in conservation planning. Climate change scenarios on the geographical distribution of species and favorable habitats of plant species. he results of the modeling of the potential habitat of some plant species in the Alborz and Zagros mountains show that in 2030 and 2080, the area of some habitats will decrease and the level of expansion of the species will be extended to higher altitudes.
One of the important effects of climate change is to create changes in the distribution range of plants, so it is necessary to investigate the effect of climate change on the distribution of plant species. Therefore, determining the prediction of the habitat of plant species using modeling methods in this direction can help in the management and exploitation of ecosystems.
In this research, by preparing a forecast occurrence map of the current and future range of A. Aucheri species under two climate warning models (Rcp4.5 and Rcp8.5 scenarios, the displacement of this species in geographical latitudes was investigated in Alborz pasture ecosystems in Mazandaran province.

The studied area is Mazandaran province, the province with an area of 2375500 hectares, occupies about 1.46% of the total area of the country. The lowest point of the province with a height of -28 meters above sea level is located in the coastal areas of the province and the highest point is Damavand peak with a height of 5610 meters above sea level in the Alborz mountain range in the south of the province. The average annual rainfall in the coastal strip of the province is equal to 977 mm. Artemisia Aucheri species is one of the representative plants of Alborz rangelad habitats and has a relatively wide spread and plays an important role in soil protection and water storage, and for this reason, it has been studied.Occurrence points (presence and non-presence) of A. Aucheri species were initially prepared using the updated map of plant types and the initial map of the distribution areas of A. Aucheri species. Then, by visiting different areas of the habitat of the species, the minimum and maximum height of distribution was determined. Also, by using the land use map, uses other than pasture use were removed from the polygons, and in the ArcGIS ver10.5 environment, the maps were modified and the current species presence map was finalized. Using 15 synoptic stations, a database, including precipitation, night temperature, daily temperature, and the average temperature was formed, and 19 climatic variables were calculated. Also, using a digital height model with an accuracy of 30 meters, three physiographic variables, including slope, direction, and height were prepared. Then, the presence and absence points of A.Aucheri were identified using updated maps of ecological zones and field visits.
Logistic regression was used to predict the habitat distribution of A. Aucheri species. In this way, the environmental variables in the logistic regression model are entered as predictor variables (independent) and the presence and absence of the species as response variables (dependent) and the vegetative behavior of the studied species in the current conditions is calculated and the relevant relationship is determined. This relationship was used to predict the habitat in 2050 using the 0-ESM2-MRI general circulation model under RCP4.5 and RCP8.5 scenarios. This method was implemented in SPSS Ver24 software and its results were converted into a map using Arc GIS Ver10.5..

The current distribution map of A. Aucheri species shows that in the western, central and to some extent eastern parts of the province, this species is observed in 75-100 percent. The lowest species presence is in the 0-25 percent class. The produced map, in four classes, showed that in 64% of the entire province, the probability of this type of occurrence is 75-100%, which is equal to 1527354 hectares. In this connection, the value of Kappa coefficient was 0.85, which according to the classification of Kappa coefficients (Ilunga Nguy and Shebitz, 2019), the model has good and acceptable accuracy. The maps obtained from the prediction of the logistic regression model show that under the RCP 4.5 scenario, the presence of the species increases in high altitude areas (2500 to 3000 meters), which includes all areas in the central, western and eastern parts of the province. The percentage of presence in the 75-100% class was observed in 60.6% of the area of the province and the highest percentage is the 75-100% class. The percentage of the 0-25% class will decrease. The RCP 8.5 scenario shows that the presence of the species in the 75-100% class will decrease in the central, western and eastern parts of the province. There is a large decrease in 0-25% class and a very small increase in 50-75% class and a large increase in 25-50% class.

Background and Theoretical Foundations: 

Climate change, as one of the greatest global challenges of the 21st century, has confronted humanity with multi-dimensional risks and consequences. This phenomenon, caused by the increased concentration of greenhouse gases in the Earth's atmosphere, has gradually had and will continue to have widespread impacts on the environment, the economy, and human societies. The rise in the Earth's average temperature, along with the melting of polar and mountain ice, has not only led to the rise in sea levels and the submergence of coastal areas, but has also severely affected natural ecosystems and wildlife. Moreover, changes in rainfall patterns and prolonged droughts have resulted in the depletion of freshwater resources and the weakening of food security in many parts of the world. These changes have also led to an increase in the frequency and intensity of natural disasters such as floods, severe storms, and wildfires, causing further economic and human losses. To address this immense challenge and reduce its damages, the global community requires urgent and extensive action. In this regard, international cooperation and shared commitments to reduce greenhouse gas emissions and adopt adaptation policies for climate change are of utmost importance. International agreements such as the Kyoto Protocol and the Paris Agreement are significant steps towards establishing legal frameworks for reducing greenhouse gas emissions and strengthening adaptation efforts. However, these agreements face numerous challenges in terms of interpretation, implementation, and compliance with obligations. Disputes over the responsibilities of countries, particularly in distinguishing obligations between developed and developing nations, are among the obstacles hindering the full implementation of these agreements.In this context, international law and international judicial bodies play a crucial role in defining and clarifying the responsibilities and obligations of countries. These institutions can contribute to improving the implementation of commitments and enhancing international cooperation in addressing climate change by providing legal solutions and judicial decisions on disputes between countries. Furthermore, the development and strengthening of existing legal regimes and the creation of new mechanisms for monitoring the implementation of obligations and ensuring countries' compliance with agreements are among the measures that can help better manage climate change.

This article examines international texts and agreements related to climate change management and analyzes and interprets international legal commitments in this area using a library-based approach..

The findings of this article indicate that international dialogue and consultative mechanisms, such as the advisory jurisdiction of the International Tribunal for the Law of the Sea, can aid in interpreting obligations, resolving disputes, and providing advisory opinions on climate change. Therefore, to enhance the effectiveness of legal tools in addressing climate change, there is a need to develop transparent laws and procedures as well as to strengthen the capacity of international institutions. Consequently, international law and judicial bodies play a key role in managing climate change. International dialogue and consultative mechanisms, such as the advisory jurisdiction of the International Tribunal for the Law of the Sea, can be valuable tools for facilitating cooperation and providing legal solutions in this area.

The agreement of the Commission of Small Island Developing States on Climate Change provides for the possibility of seeking advisory opinions from the International Tribunal for the Law of the Sea. The advisory jurisdiction of the International Tribunal for the Law of the Sea is still in its early stages and faces challenges such as determining the legal basis and the need for transparent rules to establish jurisdiction. Accordingly, the Tribunal must pay careful attention to the precise identification of "relevant agreements" and the preservation of the coherence of its judicial function when providing advisory opinions. Meanwhile, advisory proceedings of the Tribunal can serve as a tool to increase awareness, facilitate political actions, and provide legal solutions regarding climate change.

This study was carried out in the Gowatr mangrove forests in Gulf of Oman, on September 2017 and May 2018 during high tide with the aim of quantifying production, biomass carbon stocks of Avicennia marina and introduce of PnET-CN model. The results were showed that the mean of aboveground biomass was 28.09 ± 4.52 and 28.51 ± 4.49 t/ha, moreover, the mean of aboveground carbon stock was 11.22 ± 1.83 and 11.34 ± 1.7 t/ha, and the mean of primary production was 219.251 and 238.171 gC/m2.mo in September 2017 and May 2018, respectively. The estimated of the production and biomass carbon stocks using PnET-CN model was showed that the mean of production was 289.051 and 291.487 gC/m2.mo and the mean of aboveground biomass carbon was 12.29 and 12.76 t/ha in September 2017 and May 2018, respectively. The PnET-CN model could predict the effects of simultaneous changes in several environmental variables on the interactions among several ecosystem processes and it could estimate the amount of tree carbon stock and primary production with proper validation. PnET-CN model shown ecosystem models extended our understanding of the forest carbon cycle spatially and temporally and generated additional information about carbon stocks and fluxes.

The purpose of this study was to investigate the metabolism and role of gamma-aminobutyric acid as an effective compound in inducing stress tolerance in plants, in cultivars of strawberry ʻ Camarosaʼ (heat-sensitive) and ʻKurdistanʼ (heat-tolerant). For this purpose, the strawberry plants were transferred to Isfahan University of Technology on 15 November 2021 and with a fully expanded 5–6 leaf stage, they were transferred to growth chambers with temperatures of 25, 30, 35 and 40 ºC, relative humidity of 70% and 1200 lux of light. After 10 hours of temperature stress, the plants were taken out of the growth chamber and some physiological, biochemical and molecular traits were measured. In order to investigate the expression of the Succinic semialdehyde dehydrogenase gene, sampling was done at 0, 2, 5 and 10 hours after the start of a temperature stress of 40 ºC. This research was conducted as a completely randomized mixed-analysis experiment. The results of the experiment showed that high temperature (40 ºC) in cultivar ʻCamarosaʼ significantly 20.43% decrease the content of gamma-aminobutyric acid and 12.19% the amount of soluble carbohydrates, as well as 43.81% increased the percentage of ion leakage, 20.66% proline, and 200% in injury rating value compared to the control (temperature of 25 ºC). In contrast, High temperature stress (40 ºC) in the cultivar ʻKurdistanʼ caused a 17.78% increase in gamma-aminobutyric acid compared to the control treatment. Injury rating value was statistically non-significant in the cultivar ʻKurdistanʼ at a temperature of 40 ºC compared to the control. The expression level of the SSADH gene (the key gene in the entry of GABA into the tricarboxylic acid pathway) was constant in cultivar ʻCamarosaʼ, but in cultivar ʻKurdistanʼ, the gene expression level increased significantly 2 hours after heat stress.

Climate change has a direct impact on hydrological components and water resources and plays an important role in aggravating possible risks such as drought and floods. Therefore, it is necessary to investigate the effects of climate change on water components such as runoff. This study evaluates the effect of climate change on climatic parameters (temperature and precipitation) and the amount of runoff in Kiwi Chai basin from an environmental point of view. The hydrological model of the Soil and Water Assessment Tool (SWAT) was used to analyze the effects of climate change on the water resources of the Kiwi Chai basin, which is one of the Sefidroud sub-basins. Runoff simulation by applying climate change conditions for models (EC-EARTH, HadGEM2-ES, MIROC5, MPI-ESM) under two scenarios (RCP 4.5 and RCP 8.5) in three periods (2040-2021), (2041-2060), ( 2061-2080) and statistical analysis was performed to identify which climate model is more consistent with the changes in the mean and standard deviation of the historical series. An increasing trend in precipitation and a significant increase in average annual temperature were predicted in the early, middle, and late 21st century. The results of simulation of basin runoff with SWAT model also showed a significant decrease in basin runoff in future periods compared to the base period. These findings provide local water management authorities with useful information to aid decision-making in the face of climate change.

Climate change, as one of the most important threats ahead, has significant effects on biodiversity and natural ecosystems. In the present study, using species distribution modeling (SDM) the effects of climate change on the spread and distribution of the Shabout fish species (Arabibarbus grypus, Heckel, 1843) was investigated. in terms of SDM, an ensemble model by the Biomod2 package with six different algorithms for the present time and also under two-time series of 2070 and 2090 with two models Optimistic (SSP 126) and pessimistic (SSP 585) were used for a future time. In addition, eight climatic, topographic, and human variables were used to build the model. The results showed that the prediction performance of the model based on three parameters AUC, TSS, and KAPPA ranged from very good to excellent ≤0.77. The most important parameters affecting the distribution of shirbat species were the parameters of the minimum temperature of the coldest month of the year (Bio 6), total annual rainfall (Bio 12), and human footprints. Also, the range of distribution of the studied species in both optimistic and pessimistic scenarios for the years 2070 and 2090 will face a significant decrease. The effects of climate change on the shabout species have clearly shown that the species have different responses to climate change, and these responses provide appropriate and specific management strategies for each species.

Examining long-term changes in the integrity or fragmentation trends of mangroves due to climate change can lead to a more precise understanding of structural changes in mangroves and their connection to the impacts of climate change. This study investigates the changes in the integrity status of the Hara Biosphere Reserve mangroves in Qeshm in response to variations in rainfall and drought over a 31-year period (1986-2017). For this purpose, a 31-year time series of satellite images and rainfall data were used, and values for the Number of Patches (NP) and Largest Patch Index (LPI) metrics, as well as SPI values, were prepared over the period. The results of changes in the number of patches and the largest patch index of mangroves during periods of wet years (before 1998) and drought years (after 1998) showed that with the increase in SPI values (positive values) before 1998, the number of patches and the largest patch index decreased, while in the period after 1998, with negative SPI values, the number of patches and the largest patch index increased. In fact, the results indicated an increase in the extent of core areas and large vegetative patches (increased structural integrity) of the reserve during the wet period and the reverse trend during the drought period. Based on landscape ecology principles, the increase in the number of patches and the largest patch index (due to the reduction in the total area of vegetation) in the period after 1998 indicates the degradation of this habitat in recent years. The results of this study can be used to assess the vulnerability of these habitats to the impacts of climate change.

Forests are regarded as an economically viable solution to reduce greenhouse gas emissions and mitigate climate change. Carbon sequestration in forests is accomplished through surface and underground biomass as well as soil, which are interconnected and important sources of carbon storage. using direct calculations based on stem analysis and plant biomass. Four poplar plantations were selected, and a one-hectare plot was sampled in each plantation. DBH and the total height of all trees were measured in each plot, and two poplar trees were randomly selected and cut for analysis. Stem analysis, wood biomass determination, and carbon measurement were conducted. In each plot, soil profiles were dug, and samples were taken to measure the physicochemical properties. The results showed that Shaft had the highest density (N/ha) (326), followed by Siahkal (216), Langrud (129), and Talesh (190), respectively. Stand tree stem carbon content (tons per hectare) was the highest in Talesh with 52 tons per hectare, followed by Shaft (38.7), Siahkal (28.3), and Langrood (24.16). Allometric equations were established based on the highest correlation coefficient (r2) and the lowest standard error value (SE) between age as the independent variable and carbon as the dependent variable. Calculation of carbon sequestration in plantation stand stock and soil can provide insights into species function and their responses. Furthermore, comparing carbon sequestration in different sites can aid in the restoration of degraded lands and the conversion of such lands into high-yield plantations, which can be an effective measure in managing carbon sequestration using fast-growing species.

Using R2, MAE, and RMSE statistical parameters, the feasibility of the LARW-WG model for producing and simulating daily rainfall data in the study areas was examined in this study. As a result, after confirming the model's capability, the HadGEM2 atmospheric general circulation model was used to forecast the changes in rainfall in the study area for the future period of 2021 to 2040. The results showed that at the confidence level of 99% there is no significant difference between the real data and the data obtained from the model, and the model has the necessary efficiency to generate daily data. According to Elshtar stations forecasted climatic parameters, annual rainfall would rise by 3.6 to 9 mm on average, and in Aliguderz station, rainfall will rise by 0.31 to 2.33 mm on average. indicated an improvement. Additionally, it is expected that the precipitation parameter in Kohdasht station would drop from -0.70 to -3.80 mm. Elshtar station showed an increase in all seasons except for spring, and Aligudarz station showed an increase in all other seasons except for summer, with the exception of Kohdasht station, which decreased in all seasons. These findings indicate that the climate in the province of Lorestan will change drastically from the current climate during the next 20 years. Kohdasht station's findings indicate that rainfall will be less than at the other two locations.

Climate change and its consequences have become a threat to the planet, the natural and man-made environment, and it leads to an increase in greenhouse gas emissions, global warming. In recent decades, the amount of carbon dioxide in the atmosphere has increased, and this factor of climate change, such as temperature, has decreased. One of the effective factors in the management of agricultural and industrial projects is that changing the pattern of distribution and its amount, especially its decreasing trend, can play important role in determining the time of crop cultivation and water resources planning. Temperature as one of the important climatic factors, causes changes in the temporal and mechanical pattern of climatic phenomena and droughts, floods, storms and heat waves. Destructive climate change is due to a great increase or intensity of extreme weather phenomena and climatic events. In fact, extreme events rarely occur, but they have a direct impact on communities and vulnerable areas. Studies have proved that climate change is driven by simultaneous increases in evapotranspiration and changes, contributing to water cycle processes. Social and environmental impacts of extreme events are locally significant as a result and can severely affect specific sectors and locations. From a statistical point of view, climatic events, changes in the average limit and deviation of climatic indicators alters the occurrence probability of number of frost days, cold and hot days and nights, and the length of the growing season. Climate change intensify the hydrological cycle and change the amount of evaporation and transpiration and the pattern of precipitation. Climate change and global warming increase droughts and their continuation, and this change also causes uneven distribution and affects water resources. The purpose of this study was to evaluate the temporal and spatial variations of climatic rainfall indices in the central part of Ardabil province.

In this study, 11 climatic extreme indices were selected and evaluated in a 40-year period (1973-2014) to evaluate changes. At first, the required data were prepared and after processing, the values of the indices were calculated using Excel software, then the temporal trend of the indices was analyzed by ProUCL software. Evaluating the existence of a trend in the time series data is one of the important aspects of time series. In this regard, non-parametric methods are usually used due to the lack of statistical assumptions. In this research, the Man-Kendal method was used to investigate the changing process of climatic extreme indices. The non-parametric Mann-Kendall test has the ability to adopt with non-normal time series that does not follow a specific distribution. Also, this test has a small influence of the outlier values in the time series. Regarding the spatial interpolations, there are several methods to estimate the spatial changes of variables. The difference between these methods is the way of calculating the weight that is given to the observed points around the unknown point. In this research, the inverse distance weighting method was used, which estimates the values of unknown points through the weighted average of observational data with identical points.

In general, the changes in rainfall extreme indices have a decreasing trend in all stations, but it is significant in Hir station. Based on the results of interpolation maps, the indicators of maximum 1-day monthly rainfall, maximum 5-day monthly rainfall and total annual rainfall on rainy days in the central and western parts show the least and most values, respectively. Raw rainfall intensity indicators, total annual rainfall in 95% of rainy days in the northern, southern and western parts of Ardabil province show the most values and in the eastern part of the region the least values. The indicators of the number of days with rainfall of 10 mm or more, the number of days with rainfall of 20 mm or more and the total annual rainfall in 99 percent of rainy days showed the least and most changes in the east and north-west of the region, respectively. The indicators of wet period length and Rnnmm indices show the most values in the western and eastern parts and the least values in the central part of the province. The high values of number of rainy days index with more than 20 mm precipitation are related to Sablan slopes. It should be noted that the maximum length of the dry season is longer in the middle parts than in the areas of Musharraf and the north, as well as in the slopes of Sablan. The spatial distribution pattern of the maximum wet period index is also such that the maximum length of the wet period is in the stations located on the path of rainfall caused by the incoming moisture from the Caspian Sea and Gilan province, and this effect of the increase of the wet period is also clearly visible in the stations of Sablan slopes.

According to the findings of the study, the least changes in precipitation extreme indices occurred in central stations and the highest values in precipitation extreme indices occurred in stations located in western part of the study area. Overall, it can be said that assessing changes in extreme indices can be a guide in assessing climate change and its negative effects on soil and water conditions. It should be noted that the changes in extreme indicators in different regions will be different based on climatic conditions, but in most areas, the changes in extreme indicators are such that extreme events are intensified. One of the important effects of climate change is changing the rainfall regime and the pattern in the future. In many cases, changes in precipitation characteristics and extreme events may not follow the general trend of precipitation reduction. Spatial evaluations of changes in the occurrence and trend of extreme climatic indicators can help in identifying the signs of climate change. The dominant trend of increasing changes in rainfall extremes can have a significant contribution in intensifying the flood occurrence. The extreme rainfall events have undergone many changes in recent years under the influence of many factors. Considering the occurrence of severe floods under the effect of extreme rainfall events, examining the changes in the trend of these events in the past years and predicting them in the future will be effective in planning and managing water resources and natural disasters caused by these events. Forecasting changes in climatic extreme events is necessary to take effective considerations to deal with the harmful effects of climate change. In general, it can be said that the analysis of indicators related to extreme events can complement the results of evaluating the annual average values of climatic variables.

Today, climate issues threaten the security of the world, security which is considered necessary and vital in all fields and for all people. The phenomenon of climate change can affect the water requirement of crops by changing the amount of evaporation and transpiration of plants and the duration, intensity and time of rainfall. The studies related to climate change that have been conducted in Iran in recent years have focused more on climatic indicators and the effects of these changes on agricultural production have been given less attention. Therefore, assessing the effects of climate change on agriculture is an essential need. Due to the fact that Ardabil province is one of the poles of agriculture and animal husbandry and any change in the climate will endanger the lives of most of the residents of this region and will cause a change in the use of farms, pastures and the loss of agricultural production.kkkT Therefore, assessing the effects of climate

The study area is located on the slopes of Sabalan Mountain in Ardabil and East Azerbaijan provinces. Its geographical location is located at latitudes of 37 degrees and 44 minutes to 38 degrees 25 minutes and longitude 46 degrees and 22 minutes to 48 degrees 41 minutes. The minimum height of the area is 371 meters and its maximum is 4811 meters above sea level (Fig, 1). This study was conducted to influence climate change in wheat cultivation on slopes of Sabalan mountain. The important part of this research is based on statistics and information about meshkinshahr and sarab synoptic stations. In order to investigate the climate change conditions, a basic statistical period and a period as climate change should be determined. Therefore, statistical periods in this study from 1995 to 2015 and climate change period from 2016 to 2045 and 2046 were selected. Statistics about the studied stations were obtained from the Statistics and Information Bank of the National Meteorological Organization. The data taken from these statistics include: maximum and minimum temperature,daily rainfall and sunshine. to work with the LARS-WG model; First, the studied data should be sorted as Julius days. After collecting data in the Excel environment, it should be noted that there is no missing data, in case of missing, it must be encoded with -99. Aggregated data must be stored in a folder in nodpad with st extension.The address of folders stored in the N environment should be provided to the model from the option series, and the output data address should be given to the model. How to choose a scenario. First, in Excel environment, statistical data is placed in a column and in the next step, the generated data for each scenario is placed in the columns in front of each column of observational statistics, after preparing this step, the data is taken to the spss environment and correlation is taken between observational and production data. Production scenarios that are highly correlated with observational statistics are accepted as the studied scenario. CROPWAT software was used to estimate water requirement and effective precipitation. By entering minimum temperature, maximum temperature, relative humidity, wind speed and number of sunshine hours related to the plant, as well as the environment and region and its cultivation time, you can calculate the water requirement of the plant at different growth stages. Figure 2 shows the steps of data analysis in CROPWAT software.

In this study, first, the power of LARS-WG model for the basic statistical period of the years (1995-2015) was measured. The purpose of this assessment is whether the model has the ability to simulate for future periods. To do this, the tst file containing the results of comparing the statistical characteristics of the observed data with the simulated data was plotted as a diagram (Shapes, 2 and 3). The results showed that in Meshkinshahr station, the model has better efficiency for simulating maximum temperature and minimum temperature. The observed temperature and simulated temperature for 1995-2015 are similar and the diagrams are overlapping. Also, the deviation of production criteria is in the range of number one. This model is not effective in simulating the sunshine hour because it simulates the amount of sunshine hours in the first half of the year less than the actual size. In the case of rainfall, the model is better than April and May in other months. In Sarab station, the data were performed based on LARS-WG model by comparing the statistical period data and the produced data. To ensure the ability of computational data model, they were compared by model and observational data in the studied stations. Comparative results show the data of minimum temperature, maximum temperature, precipitation and sunshine in mirage synoptic stations for the base period. The capability of LARS-WG model in modeling minimum temperature, maximum temperature and radiation in these stations is completely in accordance with the observed data. The standard deviation rate is between 0.5 and 1. The results of this study show that in Meshkinshahr station, precipitation and temperature in the period 2016 to 2045 are -3.9 and +1.73, respectively, and these two variables in the period 2046 to 2065 are -6.67 and +1.80, respectively. In Sarab station, precipitation and temperature in the period 2016 to 2045 were +6.17 and -0.69, respectively, and in the statistical period of 2046 to 2065 were -12.91 and +0.37, respectively. As a result, rainfall in the coming periods is associated with a decrease in Sarab and Meshkinshahr stations, respectively. Temperatures are also rising at about 2 °C in Meshkinshahr station and the temperature increase is low in Sarab station. In comparison, Sarab plain has a wonderful state because by the period 2046 to 2065 the rainfall in this plain will decrease about 13% compared to the base period, in the same time period, wheat evapotranspiration will reach from 530 mm in the base period to 887 mm in the period 2046 to 2065. Wheat water requirement also increases from 422 mm in the base period to 810 mm, i.e. about 92%. Also, modeling shows that the average minimum temperature of this region decreases from -3 in the base period to -9.67 °C in January and from -4.3 to -8.23 in February. According to the modeling and with the decrease in rainfall in this region, wheat cultivation in this plain will face limitations in the future. However, the results of the models indicate that meshkinshahr plain is better in future periods than Sarab plain.

The purpose of this research is to estimate and evaluate the future climate change of Iran using climatic elements (minimum temperature, maximum temperature and precipitation) until the year 2100 in Iran. For this purpose, in the current research, the innovative method and tools of the algorithm and coding and NASA data to evaluate and predict the aforementioned climate elements based on two intermediate scenario (RCP 4.5) and worst-case scenario (RCP 8.5) of the Canadian CanESM2 model from the system Google Earth Engine was used under the web. In order to better analyze, investigate and compare Iran's future climate changes, the studied period of 80 years, was divided into the first 40-year period (2021-2060) and the second 40-year period (2061-2100). The results of the current research based on the intermediate scenario (RCP 4.5) indicate that the minimum and maximum; minimum temperature of the second 40-year period compared to the first 40-year period is 2.69 and 0.62 degrees Celsius, respectively, and the minimum and maximum; maximum temperature The second 40-year period compared to the first 40-year period was 3.37 and 0.91 degrees Celsius respectively; Also, based on the worst-case scenario (RCP 8.5), the minimum and maximum; minimum temperature of the second 40-year period compared to the first 40-year period is 0.54 and 3.32 degrees Celsius, respectively, and the minimum and maximum; maximum temperature of the second 40-year period compared to the period An increasing trend was predicted for the first 40 years of 2.47 and 3.46 degrees Celsius respectively. Based on the results obtained from the present research, in the studied area, the frequency of rainfall decreases in the first 40-year period and increases in the second 40-year period.

Snakebite is a global health problem and important conservation challenge. Knowing where snakebite risk is highest can help snakebite management. But climate change is altering snakebite risk pattern making its management more difficult and complicated.
In this study we used Echis carinatus’ habitat suitability as an indicator of snakebite risk, under current and future climatic conditions. We applied an ensemble of five distribution modelling methods (Generalized linear models (GLMs), Generalized additive models (GAMs), Generalized boosted models (GBMs), Maximum entropy modelling (Maxent) and Random Forest (RF)) to model the species habitat suitability. In addition, we identified villages that are at risk of envenoming form the species under current and future climate.
Results showed that the species suitable habitat will increase under climate change as consequence number of villages at risk will increase from 70247 to 82881 putting more human population at risk of envenoming.
High snakebite risk areas identified in this study are high priority target areas for awareness raising program and antivenom distribution. This study demonstrates usefulness of habitat suitability modeling in identifying high snakebite risk area in Iran.

An examination of the trend of climate data recorded in the past decades, as well as the output results of all climate models predicting the future climate, indicate the occurrence of negligible changes in the global climate. Therefore, long-term forecasting of climate variables has received much attention. In order to predict the climatic parameters in Evan Lake, downscaling of general circulation models (GCMs) was used by using the LARS-WG model. The General Circulation Model (GCM) is the most current method by using in climate change studies. They are a key to understanding changes in climate; Although GCMs are imperfect and uncertain. The LARS-WG model was implemented to predict climatic parameters and the necessary analyzes were performed on its results. After selecting the general circulation model and the scenario more in line with the climatic conditions of the region, the outputs of the selected model were compared with the base period to determine the trend of their changes. The results show a decrease in average rainfall (39.9 mm), an increase in minimum and maximum temperatures (0.4 ° C) and an increase in the number of wet days (7 days) and the number of frost days (5 days). Also, the number of dry days (7 days) and the number of hot days (5 days) will decrease in the climate period 2030-2020.

Although climate change is expected to affect many parts of the environment, water is the most critical factor affected by climate change. Iran is always facing limited water resources, and due to the fact that climate change can be considered an aggravating factor in the water crisis, projeting the effect of climate change on the future drought is very important for managing water resources. In this study, the effects of climate change on the meteorological drought of Karkheh basin in the future have been investigated by dynamical model (PECIS) and under A2 and B2 emission scenarios.

In this study, PRECIS dynamic downscaling model was used to estimate precipitation and temperature in the base period (1960 to 2000) and future period from 2070 to 2100 and under two scenarios A2 and B2. For this purpose, the PRECIS model was implemented with a horizontal separation of 0.44 degrees in grids. To use PRECIS model results, it is necessary to evaluate the model first. For this purpose, the model was first run for the 1960 to 1990 years and the projected precipitation and temperature values were compared with the observed values of the stations. The study of climate changes in Karkheh basin showed that under scenario A2, the amount of precipitation will increase by about 11% and the average minimum and maximum temperature will increase by about 5 degrees. For scenario B2, the amount of precipitation will increase by about 7% and the average minimum and maximum temperature will increase by about 3 degrees.Then, using SPI index drought analysis was performed. The variability of SPI index for 1, 3 and even 6 months is very high compared to the average because any amount of rainfall can change the value of the index quickly in this time scale. This is while the 12-month index can better determine the number of drought events and evaluate their duration and intensity. Therefore, to investigate the meteorological drought in the study area, the 12-month SPI value was used as an annual drought index.In order to investigate the characteristics of droughts, two selected stations in the region, Khorramabad and Kermanshah stations, which are the closest points to the output grid of the climate model, have been used. The choice of these two stations is due to the fact that in order to compare the drought characteristics of the base period with the drought of the future period, the rainfall data simulated by the climate model which is in the form of a grid (raster) should be used and in order to be able to compare It is necessary that the output grid points of the model match the stations as much as possible in terms of location. Therefore, by adapting the stations on the network of output points of the climate model, two stations, Khorramabad and Kermanshah, which are the closest points to the output grid of the model, were selected. The study of meteorological drought using the SPI index shows that several major droughts occurred in 1966-67, 1970-71, 1973, 1977-78, 1984, 1991, 1995, 1998-2000. The study of drought during the period 2070 to 2100 in Kermanshah and Khoramabad stations shows that under both scenarios, the years 2077, 2081 to 2083, 2087 to 2089, and 2095 to 2096 will experience drought. However, in both scenarios, the intensity and magnitude of the drought will decrease compared to the base period, and this decrease is greater under scenario B2 than A2. The results also show that the number of dry months and the duration of drought will increase in both scenarios. Examining the probability of drought occurrence under different scenarios shows that the probability of drought occurrence for Kermanshah station is equal to 9% under scenario A2 and 15% under scenario B2, which is a decrease compared to the probability of occurrence of drought in the base period of the same station. The probability of drought for Khorramabad station under scenarios A2 and B2 are 12 and 19 percent, respectively, and the same probability is 15 percent for the base period of Khorramabad station. Comparing the probability of occurrence for different scenarios shows that the occurrence of drought under scenario B2 will be associated with a higher probability than scenario A2.

Investigating the effects of climate change on the meteorological drought of the Karkheh basin by dynamic climate model during the period from 2070 to 2100 shows the following results in brief:The evaluation of scenario A2, during the period from 2070 to 2100, shows that the average rainfall will increase by about 11%. On the other hand, the average minimum and maximum temperature under scenario A2 shows an average increase of 5 degrees in all months. Meanwhile, the projected rainfall under the B2 scenario has shown an average increase of about 7%. Under scenario B2, the average minimum and maximum temperature has increased by about 3 degrees Celsius.Study of climate change on the meteorological drought of Karkheh Basin shows that the most number of droughts occurred in the stations are 1 to 3 month droughts; Events of 4 to 7 months also show a significant number in stations. The study of meteorological drought during the period from 2070 to 2100 shows that under both scenarios A2 and B2, the severity of droughts will decrease compared to the base period, although the duration of drought and the number of dry months will increase. Examining the probability of drought occurrence under different scenarios shows that the probability of drought occurrence under scenario A2 and B2 will decrease in the region. Comparing the probability of occurrence for different scenarios shows that the occurrence of drought under scenario B2 will be associated with a higher probability than scenario A2.The results show that to evaluate the drought, the SPI index three and six months shows large variability in most of the stations. Therefore, according to these variabilities and the fact that in order to study drought changes in future periods, the output data of climate models, which are usually less accurate for short-term periods, should be used, to study the meteorological drought from the SPI index 12 months was used.

Mangroves are the most efficient coastal environments for carbon sequestration, which can play an effective role in modification of increasing greenhouse gases. In this study, for the first time, the carbon storage in soils and mangrove trees in mangrove forest of Govatr Bay were evaluated. The amount of sediment carbon in sediment cores was determined as well as the diameter on breast height and height of trees were measured in 12 stations in Bahu and Govatr Estuaries. Satellite imagery showed that the total area of the Govatr Bay mangrove forest is 450 ha, 67% of which is high density forest. The amount of soil carbon in the region fluctuates between 1.9 to 3.8%, which is in the range of the global average (2.2%). The average carbon content of the top 1m of Govatr Bay is 393 tons per hectare (t ha-1), which is 30% higher than the global average. The total amount of carbon in top 1m of Govatr mangrove soil was estimated at 177,000 tons, 70% of which is sequestered in Bahu Estuary mangroves. The total amount of soil carbon in Govatr and Bahu Estuaries is 121600 and 210500 tons, respectively. A total of 64,100 tons of carbon is stored in the mangrove trees of Govatr Bay, 64% of which are related to the Bahu Estuary. A total of 376,000 tonnes of carbon (equivalent to 1,378,000 tonnes of carbon dioxide) has been stabilized in the Govatr forest, only 11% of which is stored in trees. Estimates show that if the Govatr are completely deforested, more than 279,000 tons of carbon dioxide will re-mineralize into the atmosphere.

Temperature is one of the fundamental elements of the climate of an area, whose transformation can transform the climate structure of any place, for this reason, the study of the temperature trend in different temporal and spatial rules occupies a large part of climatology researches. Most of what is referred to as global warming or climate change includes mostly warming changes and the upward trend of the three components (average, minimum and maximum) of air temperature. Currently, climate threshold phenomena are in the center of researchers' attention because the risk of increasing the frequency, duration and sensitivity of climate thresholds has increased due to the increase of greenhouse gases and aerosols in the atmosphere. The LARS-WG model is a model that downscales the output of GCM models.Researches that focus on the temperature parameter; It is increasing day by day, among them is the research related to the increase in frequency, intensity, recorded global warm periods and the continuity of heat waves, which was done by Perkins et al. (2012). Yu et al. (2019), in their study investigated the temperature changes in the world and the results showed that the temperature anomaly is higher in the oceans and southern latitudes compared to the land and northern latitudes. Hu and Huang (2020) investigated the high temperature anomaly and its relationship with the general circulation of the atmosphere, and the results of their research showed that the highest temperature anomaly occurred in the Arabian Peninsula. Rohbakhsh Sigaroudi et al. (2017) investigated the anomaly of the average minimum and maximum temperature of the warm period of Iran in the period (1951-2010) and concluded that the western half of the country had the largest decrease in the average minimum and maximum temperature. Karmi-Mirazizi et al. (2018) investigated the synoptic patterns that lead to temperature anomalies and thermal changes in the western and northwestern regions during the statistical period (1989-2018). Rababi Sabzevari et al. (1401), in the west and northwest of Iran, analyzed the synoptic patterns that lead to temperature anomalies for 1989 to 2018, and the results indicate the existence of the mid-latitude meridional current as the main cause of temperature anomalies.

Ardabil province is located in the northwest of the Iranian plateau with an area of 17,953 square kilometers and has the coordinates of 37 degrees 7 minutes to 39 degrees 43 minutes north latitude and 47 degrees 19 minutes to 48 degrees 55 minutes east longitude. In this research, in order to achieve the goal of the research, the long-term statistics of the minimum, maximum and daily temperature averages of the selected synoptic stations of Ardabil province (Ardabil, Pars Abad and Meshginshahr) were analyzed. For this purpose, first, the different intensities of the temperature anomalies of the stations were calculated based on the data of 1980-2020 using the Z index. Then, to generate the data of each station under the conditions of climate change, after the preparation and quality control of the data, the variables of minimum and maximum temperature, precipitation and sunny hours were entered into the LARS-WG model on a daily basis and following the evaluation of the ability of the LARS-WG model in simulating the data observed in these stations, the data of the future period (2021-2021) of these stations was produced, and the ability of the LARS-WG model in simulating the data observed in the synoptic stations of Ardabil province was evaluated. This process is divided into three stages, which include spatial analysis, model validation, and generation of synthetic weather data. The model used is CanESM2 under RCP scenarios. The daily minimum, maximum and average temperature data of synoptic stations during the past statistical period (from 1980, 1985 and 1995 to 2020, respectively) were used to evaluate temperature changes and anomalies in the coming decades (2021-2100) And the frequency of each of the temperature anomaly intensity ranges of the three studied variables was counted and their percentage was calculated. Temperature anomalies were calculated using Z index.

The comparative graphs between minimum and maximum temperature observation data values and their values produced by LARS-WG model for selected stations of Ardabil province confirm the existence of a small difference between these two data and show the high efficiency of this model in simulating Creating the studied variables and producing synthetic air data. The evaluation of the frequency of anomalies of the three components of temperature in this province under three RCP scenarios showed that in the hot months of the coming period, warm anomalies are predominant (more than 50%) and normal conditions are second (30 percent) and cold anomalies have the lowest percentage.The predicted frequency of temperature anomalies using the CanESM2 model fine-tuning under the average scenario (RCP4.5) is higher than the optimistic scenario (RCP2.6) and under the pessimistic scenario (RCP8.5) is higher than the average scenario. The difference between the estimates of the RCP8.5 and RCP2.6 scenarios and the maximum difference between the two hot and cold anomalies reaches its maximum in August. The highest and the lowest percentage of average warm anomaly frequency belong to Pars-Abad and Meshkin-Shahr, respectively. The highest percentage of cold anomaly was calculated in Ardabil and the lowest in Pars-Abad.The order of the different intensities of the temperature anomalies of the three studied components in Ardabil province under the RCP4.5 scenario, from the highest to the lowest percentage, is: normal conditions (31%), moderate heat (29.4%), weak heat (21.4 percent), very hot (6.5 percent), slightly cold (6.1 percent), moderately cold (4.2 percent), very cold, extremely hot and extremely cold (about 1.5 percent)). It can be observed that among the types of temperature anomaly intensities, there is a predominance of moderate heat and weak heat, and extremely hot and extremely cold anomalies are rare and include about 1%. In the other two scenarios, the percentage of warm anomaly prevails over normal conditions and cold anomaly.In the RCP2.6 scenario, the warm anomaly has the highest frequency in August and the lowest frequency in October, and the cold anomaly has the lowest frequency in August and the highest frequency in September. In the RCP8.5 scenario, the warm anomaly is more frequent in August and July and the cold anomaly is more frequent in May and June.