The aim of this research is to analyze the performance of 8 drought’ s index in Isfahan, Kerman and Yazd province and choose the best index. For this purpose, used monthly and yearly rainfall data in the period of 30 years (1985-2014) and also used 8 drought indexes in 20 meteorological stations of central Iran which the accuracy of each index in determining drought is examined. Also zoning in ARC GIS 9. 3 has done for driest year in the time period. And it has performed according to the best selected index. For choosing the best index in annual and monthly scale has used the efficient measure of minimum precipitation occurrence year with severe droughts in region’ s stations. The results showed that in the monthly scale only 6 and 12 months of SPI index in order to analyze the drought even in low rainfall months which confront with zero data contains. In this temporal scale, static indexes such as RAI and DI in all the stations showed the minimum precipitation year according to severe droughts and named as the best index. Also the weakest index belonged to NICHE that had not the ability of determining the drought intensity in all the study’ s region. In comparison the performance of RAI and SPI determined which RAI index showed the severe drought in all the study’ s region but SPI index could not show the severe drought category in the period of 30 year in the region of central Iran in some stations.

The use of green cover temperature for plant irrigation planning is one of the methods that has been considered by researchers. For this purpose, several indicators have been presented, among which we can mention the water stress index of the plant by Idso method. In order to plan summer corn irrigation in climatic conditions of Ahvaz using green cover temperature, in 2018 research in the research farm of Shahid Chamran University of Ahvaz Faculty of Water Engineering under four types of irrigation regime including I0, I1, I2 and I3 respectively 120, 100, 80 and 60% of the plant's water requirement was done in a completely randomized design in three replications. Based on the results, the equation of the upper and lower base line for the corn plant, treatment I1 (100% water requirement) for the development stage is 2. 89 and (Tc-Ta) ll = 1. 984-0. 0946VPD, for the middle stage is 3. 4 and (Tc-Ta) ll = 3. 217-0. 1669VPD and for the final stage of growth was equal to 1. 2 and (Tc-Ta) ll = 1. 147-0. 160VPD was obtained in degrees Celsius. The results also showed that the total water stress index for the growth period for the 120, 100, 80 and 60 treatments was 0. 17, 0. 22, 0. 35 and 0. 52, respectively. The relationship between plant water stress index and soil moisture level for different irrigation treatments was highly correlated and the equation of soil stress index with soil moisture for I1 treatment for the next day and before irrigation was equal to CWSI = 1. 8296-0. 0586ɵ, v and CWSI = 1. 038 0. 0281ɵ, v was obtained. The results showed that with decreasing water consumption, the plant's water stress index increased and with increasing water stress, the correlation between CWSI index and soil water depth decreased so that the highest R2 (0. 97) in I0 treatment and the lowest R2 (0. 88) was in I2 and I3 treatments. As the results of this study confirm, the plant's water stress index is a good tool for irrigation planning and optimal management in the field.

Some of the plants in the nature always distribute in the specific region and could rarely be observed in other climates. These plants can be used as the index for recognizing and categorizing of climates. In this research at first the climate of Markazi province were classified by using the methods of Koppen, Stenze, Emberge, Thornth waite (1948 and 1933), adjusted Demarton and Gorszinsky. For this purpose the 20 years climate data were collected and dependency relationships of climate factors with elevation were determined. In order to relocating obtained relationship in climate equations as well as establishing the classified system. In next step, were recognize the key plant species in the area. With study of 550 key plant species, 54 plant sp. were recognized as a climatic discriminates. After that the comparison of plant discriminate of climate and climatic classes of classification systems for each plant carried out. For this purpose, the methods of census correct observation and scoring them according to their importance were applied. The results showed that the obtained climatic classes of adjusted Demarton, Thornth weite, Emberge were respectively more precise than other systems in the study area. Finally the results were examined using the none-parametric test of Man-Vitni. On the basis of this analysis, significant differences also were observed between the treatments.

ABSTRACT Today, climate change and its obvious negative effects on ecosystems have caused concern. This research seeks to test whether vegetation changes are sensitive to climate shocks and also how the ecosystem recovery process is through this index. In this regard, by using the GEE platform, Java coding, GIS and statistical analysis, vegetation and Palmer indices were calculated and based on time series climate data, vegetation and climate changes were presented. The results of Palmer's drought index show that during the statistical period (1985-2020) the study area is facing drought or is moving towards drought. Also, the results indicate the longest period of drought in the region from 2013 to 2020. Totaly from 420 evaluated months, the NDVI index is below the change threshold in 70 months. Among these, 31 months of the study period is below the acceptable threshold in green and non-reservoir seasons, which is ecologically worrying. The distribution of the vegetation index based on hexagons in 1985 and 2005 had a normal and almost normal distribution; But in 2020, the graph deviated from the normal state and skewed towards the vegetation cover index under stress or even thin covers. According to the analysis of the indicators, it is predicted that the Gorgan region is on the border of such ecological developments and the historical ecosystem of the region is moving towards new ecosystems or being in a new equilibrium state with climatic conditions and human disturbances Extended Abstract Introduction Today, climate change and its obvious negative effects on terrestrial ecosystems have caused great concern to humans. These changes are effective on vegetation performance, plant distribution patterns, and have economic and environmental consequences. Therefore, it is important to know the behavioral pattern of vegetation changes against climate changes. Reviewing the studies of scientists in the world shows many researchers have used the NDVI index to study temporal and spatial changes in vegetation and its relationship with the climatic index of precipitation in different parts of the world. Studies have shown that NDVI follows precipitation with different time scales. Surveys showed that there are very few studies on determining the threshold of changes in the vegetation cover index in the face of climate shocks. Determining these thresholds can provide a suitable solution for evaluating the state of the ecosystem, the consequences of climate shocks and the reversibility or disturbance in the ecosystem. This study was conducted with the aim of improving our understanding of the dynamics of vegetation in the forest city of Gorgan during 1985-2020 against climatic stresses.   Methodology The current research is a comparative and monitoring research and seeks to test whether changes in vegetation cover are sensitive to climate shocks and also how the ecosystem recovery process is through this index. To achieve the gole, first, NDVI index was selected among the optimal vegetation indices and its calculation process was done as a time series in the GEE system. In parallel with those climate shocks, the main elements including temperature, precipitation and storm were calculated during the historical process of 35 years and the average and standard deviation statistical indicators were calculated for them and the trend of changes in the thresholds was determined. The results of climate plots and climate changes show that in the years before 1985, 2005 and 2020, drastic changes have occurred in climatic elements and climatic factors. Therefore, these years can be considered as the periods when the climate shock happened.. Next, the region was divided into 436 hexagons and the NDVI index for each of the hexagons was calculated and modeled for the years 1985, 2005 and 2020 as selected years affected by climate shocks. In conclusion, to analyze the trend of changes in the time series of the vegetation index and compare the behavior of its changes with climatic indices, the Palmer index was calculated.   Results and discussion The results of climate change monitoring based on the Palmer index showed that during the statistical period the study area is facing drought in most years. The most severe climatic fluctuations and drought in the region were recorded in 2018 and in the months of October to December. The longest period of drought has also prevailed in the region from 2013 to 2020. During this period, rainfall, temperature and storm fluctuations have the most changes. The results of drought monitoring show that in 270 months, the region is facing climatic drought stress, 57 months of the study period, the region is facing severe and very severe drought stress. The results of the time series of the NDVI vegetation index showed that, out of the 420 evaluated months, 70 months of the year the NDVI index is below the change threshold, 31 of which are in the green and non-accumulating seasons, the seasons when the vegetation is expected to be at its maximum. Placing below the acceptable range means crossing the ecological thresholds and challenges the recovery and restoration of the ecosystem, also the ecological performance will be affected at this point. Based on the assessment of the Palmer index, from 2014 to 2019, the situation of the Palmer index is in the extreme drought range. Also, since 2015, i.e. with a one-year time delay, NDVI index has experienced the lower limit of the equilibrium threshold of vegetation cover. These conditions are also valid for the years 2008, 2009, 2002 and 1997. In general, it can be said that the vegetation cover index is dependent on climatic changes and fluctuations and shows high sensitivity to changes. The important point in this section is that in the years when the NDVI index changes are at the lower limit of the threshold, we witness the most climate shocks and temperature changes, the occurrence of severe storms and precipitation fluctuations. The distribution of the vegetation index based on hexagons in 1985 and 2005 have a normal distribution; but in 2020, the graph has deviated from the normal state and skewed towards the vegetation cover index under stress or even thin covers. The visual interpretation done on the vegetation cover index in 1985 confirms the condition of the vegetation cover in the southern and western limits of the region in a state with suitable dense and pasture vegetation and forest cover on the edges. However, in 2005 and 2020, this cover has been changed and mainly turned into agricultural land and poor rangeland. In such a way that in 2020, the situation of the region has revealed the critical state of vegetation. The vegetation cover index in the central areas of the city has also reached from a relatively favorable situation in 1985 to a critical situation with almost no dense and stress-free vegetation cover in 2020. The results of the present studies are consistent with the studies of Visentr Serrano et al. in 2013 and confirm the relationship between NDVI vegetation and climate change. In addition, the results of the studies are consistent with the studies of Alwesabi 2012, Xiai & Moody, 2005 and Yan et al. 2001. In such a way that the present study and the aforementioned studies all confirm the influence of the vegetation index on climate fluctuations and precipitation with a one-year time difference.       Conclusion In general, the threshold is defined as a border with different conditions. After crossing the thresholds, the stability and positioning of the NDVI in the equilibrium range is often difficult, and the ecosystem is constantly spending energy to restore itself or to position itself in a new stability state. The result of the mentioned disorders is the reduction of resilience and resistance in the region, which leads the ecosystem to alternative states or crossing the threshold or being in a new equilibrium state. The results showed that the areas where green vegetation is concentrated and denser are less affected by climatic stresses and show more resilience. However, the areas that have become spots and islands due to destruction in the urban areas are more affected by climatic stress and destruction and show less tolerance against the destruction factors. The results help managers to focus their management plans for the preservation and maintenance of urban green spaces as well as forest and pasture ecotones on the edge of the city by knowing the thresholds.   Funding There is no funding support.   Authors’ Contribution Authors contributed equally to the conceptualization and writing of the article. All of the authors approved thecontent of the manuscript and agreed on all aspects of the work declaration of competing interest none.   Conflict of Interest Authors declared no conflict of interest.   Acknowledgments  We are grateful to all the scientific consultants of this paper.

Climate is so important for the life and development of the living organisms on Earth. Among all the effects of different atmospheric variables on human comfort, the effect of combined wind and temperature is of particular significance. In this study, using statistical data of minimum temperature and wind speed of the synoptic stations during the period 1374 to 1393, which were obtained from the Meteorological Organization, the chill wind was zoned in the country. Results that were obtained from data analysis of 120 to 314 synoptic stations (for different time intervals) showed that we can consider the months of Aban to Farvardin as the start and end of wind chill in Iran, respectively. For days of Aban to Farvardin, the average reduction in minimum temperature of 4 degrees Celsius in Bahman due to the wind blowing has been felt. Zoning maps of the country that were traced for the cold months (from Aban to Farvardin), showed that the difference between minimum air temperature and the temperature that can be felt on human body (wind chill) is meaningful as Well (Level of significance is in the range of 0.51 to 0.74). The highest frequency of wind chill is related to the year of 1390 with 18088 cases from 330 stations that are under study and the lowest is related to the year of 1374 with 4321 cases. It should be noted that from the base year (1374) onwards, the frequency of the wind chill occurrence has increased and the numbers of cold days because of the wind existence in the cities of the country are increasing too. By investigating the frequency of wind chill occurrence in the months which are under the study, the month of Bahman with 47219 cases from 350 stations and the month of Aban with 17728 cases from 305 stations, had the highest and the lowest frequency of occurrence.

The upcoming study investigates the design and use of vertical-axis wind turbines for power extraction in Chahnimeha, Zabol. In Sistan and Baluchestan provinces, due to the vastness and climatic barriers, the use of renewable energy can greatly contribute to the well-being of people. Using the meteorological data of this province, the average wind speed in the Chahnime region is estimated at 6.4 m/s. At first, 4 airfoils with the highest lift-to-drag coefficient have been selected and studied for wind turbine design. By choosing the best airfoil among the four examined ones, a wind turbine with 3 different blade sizes and rotor radius was designed. The wind turbine, which is designed with a blade length of 3 meters and a rotor radius of 1.5 m, has the best performance. The vertical axis wind turbine has been investigated in 4 models with 3, 5, 7, and 9 blades. The power factor of the 3-bladed turbine is equal to 0.30, and of the 7-bladed wind turbine is equal to 0.45. Among the examined wind turbines, the best wind turbine with 7 blades was chosen. The reduction of wind speed before the blades is influenced by the solidity of the wind turbine. The study of wind turbine exergy was used to investigate the environmental effects such as humidity and temperature on the performance of wind turbines in the climatic region of Zabol. The exergy efficiency of the designed 3-blade and 7-blade wind turbine is equal to 45 and 75%, which shows the effect of temperature and relative humidity on the wind turbine efficiency in a climate region. The results of this study clearly show that it is possible to use a 7-blade vertical axis wind turbine to provide electricity to areas far from the grid and to produce scattered.

Purpose: Estimating wind chill index as one of the indexes effective in body comfort, specifically for athletes and tourists interested in winter sports.Methods: Meteorology data including temperature and the percentage of relative humidity of 6 synoptic stations of Chaharmahal-Bakhtiyrai province, Iran from 1990 to 2007 were extracted from Iranian Meteorology Site. In order to calculate the values of wind chill, the innovative formula of NOAA Meteorology Services Center [T (WC) = 35.74+0.6215T-35.75V+0.4275TV] was used.Results: After analyzing wind in all stations, it became evident that the great percentage of wind calm related to fall, and spring had the most wind distortions. In studying the mean temperature during this studying period, Koohrang station with mean of 9.8oC was identified as the coldest station and Lordegan with a mean of 17oC represented the warmest station of the region observed. According to degrees derived from wind chill index, Koohrang station in January with a mean of -28.75 was known as the coldest and roughest station.Conclusion: Among the studied stations, Koohrang had the most intensive degrees of wind chill occurrence and Lordegan had the calmest conditions. Therefore, athletes and tourists should use warmer clothes and covers in cold seasons in Koohrang in comparison with other studied regions, in order to protect themselves from the negative effects of sudden cold and occurrence of intense wind chills.

Introduction Climatic conditions have a significant impact on human living conditions and comfort. From the earliest times, humans have reacted to fluctuations in weather conditions Therefore, it has designed its living environment in accordance with the climatic conditions. One of the most important measures in identifying a comfortable climate is to assess the conditions of the human living environment. Which determines the level of human comfort in the environment. Meteorological variables and bioclimatic indicators are needed to assess the conditions of human comfort in the environment. . Therefore, urban planners and regional planners need useful and at the same time practical indicators in order to optimize the environment and determine the best time for human comfort. Human comfort conditions provide very good information for planners by evaluating bioclimatic indicators. The information obtained from this research provides appropriate suggestions and strategies for improving the situation in each region. To know the range of comfort climate (optimal and optimal climate) can not be enough to describe the climatic elements of the region, including temperature, humidity, wind and radiation. Rather, the type of climate in terms of comfort or lack of thermal and climatic comfort should be determined quantitatively in the form of a general indicator and a combination of all these climatic elements. Many factors affect the tourism industry, one of the most important of which is the climate. Climate plays a role as one of the most important local resources in the tourism industry. Awareness of climatic comfort plays an important role in human life and activities, and physiological comfort is closely related to climatic factors. Therefore, the study of climatic parameters affecting the climatic comfort of work seems necessary. Gilan province is one of the most populous regions of the country and ranks first in the country in terms of population density. In addition to various economic activities, this province hosts millions of people from all over the country every year due to the existence of various attractions (especially the Caspian Sea). And it is one of the touristic provinces of the country And studying the climate comfort of this province can be an important step in planning for tourist reception and its requirements. In this study, the climatic comfort of Gilan province has been studied. Materals and methods For this purpose, climatic data from 11 synoptic stations (Rasht, Astara, Anzali, Deilman, Kiashahr, Lahijan, Manjil, Masouleh, Jirandeh, Talesh and Rudsar) including monthly average temperature, average maximum and minimum temperature in degrees Celsius, The monthly average of relative humidity as a percentage, the average of sunny hours and the number of rainy days during the statistical period of 1995 to 2020 have been received from the Meteorological Organization of the country. Then in SPSS software, Excel database was created And processed the data and calculated the average of all the mentioned parameters on a monthly basis And deficiencies were corrected And through the Tourism Climate Comfort Index (TCCI), the calculations are performed And after sorting and analyzing the climatic conditions, the study area has been studied Thus, based on the Tourism Climate Comfort Index (TCCI), zoning maps of the province were drawn in GIS software. Finally, the results are analyzed and interpreted as maps. Results and discussion April, south of the province (Manjil), May, center, Caspian Sea coast, part of the northeast and south of the province (Rasht, Anzali, Lahijan, Deilman, Jirandeh), August, east of the province (Rudsar), September, center, East and part of the south of the province (Rasht, Rudsar, Deilman) and October, south of the province (Jirandeh) has pleasant and favorable conditions. All tourism activities are recommended to tourists. Conclusion The results of the conducted investigations show the existence of various types of comfortable weather conditions for tourism in Gilan province. The months of May and June in most parts of the province have very favorable and pleasant conditions and the climatic conditions are suitable for all kinds of tourism activities. In the cold season of the year (January, February and December) in all parts of the province (especially the high areas such as Dilman and Masuleh, etc. ), very unfavorable (cold) conditions prevail, and in the hot season of the year (July and August) the conditions are It is very unfavorable (heat) in most of the studied areas (especially coastal areas due to high humidity). All in all, in this research, all kinds of tourism activities have been targeted according to each season and each region.

Climatic unfavorable conditions lead to limitation of activity. Therefore, application of climatic severity coefficient can lead to befitting distribution of economic potentialities. The climatic stress index is suitable scale for ranking of residential sites due to climatic severity coefficient. In this research by dint of ArcGIS 9.1 software, climatic data were analyzed and numeric maps of climatic stress index in cold and warm seasons were produced by Inverse Distance Weighted (IDW) interpolation method. Thereafter, quantity of these indices were extracted from the map on the basis of cites geographical location. Then cites of this Province have been ranked from 1 to 25 in cold and warm seasons out of consideration of index. Results of this research show that the climatic stress index can be used to give climatic hardness coefficient in any location. Investigation of mean of stress index in 25 sites of this Province show that, not only the number of cold months is more than those of warm month, but also hardness of cool in seven months of cold season is more severe of that in five months of warm season. Studying of monthly mean of climatic stress index shows that, Boldaji, Nafch and Chelgerd sites in cold season and Malkhalife and Lordegan sites in warm season have more hardness of climatic conditions.