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In this study, in order to study the base temperature (minimum temperature for plant growth) at the degree of growth day (GDD), which is one of the important parameters in calculating the degree of growth day, first, the data required for the 2009-2017 statistical period of wheat production at the station Sararood was taken from the station. Then, after sorting and separating growth different stages, using four methods of calculating the base temperature (1 - minimum standard deviation SDgdd day, 2 - minimum standard deviation SDAY days, 3 - regression coefficient per day CRday, 4 - CV coefficient of variation) was the most suitable method for calculating the base temperature of growth in different stages of planting to wheat harvesting. The results showed that the most suitable method is the minimum standard deviation in GDD, which The base temperature was obtained from germination to full reach for different growth stages, 5/8, 0/38, 1/8, 2/6, 0/63, 2, 3/7, 9/7, 8/6, 11 degrees Celsius. By comparing different methods of calculating GDD, the most appropriate of method was the general method of calculating the degree of growth day due to the most of similarity to the station data. The degree of growth day in different stages was calculated based on their base temperature and the results showed that the calculation of the base temperature at each stage of the growth of the wheat was very accurate for GDD calculation and a precise estimate of GDD was obtained.

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The purpose of this research is to identify changes in the temperature trend in the western half of Iran. For this purpose, monthly temperature data of 15 synoptic stations were collected during 1960-2010. Quality control was applied on these data by applying Pettit, SNHT, Buishand and Von Neumann’s tests. Later data Simulated and compared with reanalysis data such as ERA-Interim, ERA-20C, NCEP and CMIP5 models (RCP8.5 for the period 1960-2100). Trends were calculated by the Mean Kendall test and the Sen’s estimator (95 % confidence level). Based on the results obtained from all models, a significant positive trend was observed in spring, summer and autumn, and only in winter according to ERA-Interim. Based on CMIP5 results for the period 2050-2100 values between 2 and 4 ° C/100 achieved, which is lower than the results of other models for the period 1979-2010. Considering the CMIP5 models and their overall average in the study area, an increase in annual temperature (7 ° C /100) for the second half of the 21st century was confirmed.

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Air pollution is one of the major problems in large cities, which can be harmful to human health and the environment. Isfahan is one of the most polluted cities in Iran.
 Its geographic location and low wind speed, industrial activities, transportation, agriculture, and other human activities have created critical air pollution conditions for the city. Nitrogen dioxide is an important pollutant of air pollution, which is monitored using ground stations and satellite measurements. In this paper, daily data of nitrogen dioxide from Ozone Monitoring Instrument (OMI) satellite sensor, wind and surface temperature of Isfahan Meteorological Station data were used between October 2004 and May 2016. The average amount of nitrogen dioxide in the measured range is .The highest amount of nitrogen dioxide ( ) was observed in December and the lowest ( ) was observed in July. The standard deviation of the winter season ( ) is higher than the summer season ( ). The correlation coefficient of nitrogen dioxide with wind and temperature was -0.41 and -0.54, respectively, which indicates the higher importance of temperature in nitrogen dioxide changes. After the formation of the time series, the average monthly nitrogen dioxide content was determined using spectral analysis of least squares of statistically meaningful peaks corresponding periods. These statistically meaningful peaks corresponding periods have been eliminated from the mean monthly nitrogen dioxide time series, and with the linear fit on the residual time series, the trend has been calculated. The nitrogen dioxide trend for Isfahan is per year with 95% confidence.
 

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Heat waves are important phenomena in Iran, And its upsurge in recent years seems to have a high upside trend.This climate has a negative impact on agriculture, forest fire and forestry, water resources, energy use and human health.The purpose of the research is to explain the frequency, time distribution, continuity of thermal waves, and the identification of its occurrence in the southern foothills of central Alborz.Therefore, using the statistical methods and maximum daily temperature data of Tehran (Mehrabad), Qazvin and Semnan stations for the statistical period of 30 years (1966-2016), the mentioned characteristics were extracted.In the first step, the nonparametric method of Kendal was used to understand the variability and awareness of the monthly trend of maximum temperatures in the study period.In order to determine the severity, duration and frequency of heat wave events, the percentiles (95.98) and normalized temperature deviation (NTD) were used.The results of the study showed that the frequency of short-wave heat waves was higher.Most frequencies are related to 2-day waves, respectively, and Tehran (Mehrabad), Semnan and Qazvin stations are more frequent.The highest frequency of annual events was detected at stations in Tehran (11 waves in 2010), in Semnan (9 waves in 2015) and Qazvin (7 waves in 2015), respectively.The highest frequency of monthly heat wave events was recorded in June and September.The highest continuation (15 days) was obtained in March 2008 with the percentile method at Mehrabad station.In the normalized deviation method, the temperature was calculated as a warm wave (12 days) in 2008.The highest annual frequency of heat loss occurred in all three stations in 2015.The evolution of the process indicated an increase in the incidence of thermal waves in the cold period of the year But in other chapters, no meaningful changes were made.As it says, the decline in cold winter temperatures is on the southern slopes of Alborz.The results of the two methods showed that in the normalized deviation of the temperature, the number of thermal waves more than the percentile method was recorded, but in the percentile method, the thermal wave was more prominent in the cold period of the year.

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Abstract
In recent years, attention has been paid to climate change, which could be the result of economic, social, and financial losses associated with extreme weather events. The purpose of this study is to investigate the variation of extreme temperature and precipitation in Kurdistan province. For this purpose, daily rainfall data, minimum temperature and maximum temperature of 6 stations were used during the statistical period (1990-1990). And their changes during the period (2041-2060) using the universal HadGEM2 model under two scenarios RCP2.6 and RCP8.5 and the LARS-WG6 statistical downscaling were investigated. In order to study the trend of climatic extreme indexes, rainfall and temperature indices were analyzed using RClimdex software. The results showed that during the period (2016-1990), hot extreme indicators have a positive and incremental trend. This trend is significant for the "number of summer days" and "maximum monthly of maximum daily temperature" indicators. This is while the cold extreme indexes had a decreasing and negative trend. This trend was significant only for the "cold days" index. Extreme precipitation in Kurdistan province has a negative trend in most stations. ،this trend is significant at most stations, that indicates a reduction in the severity, duration and frequency of precipitation during the study period. The results of the climate change outlook also indicate that the temperature will increase over the next period and rainfall will decrease.
 

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Objectives: The purpose of this article, the relationship between maximum temperature of Kerman province geopotential height at 500 hPa to avoid risks and losses are extreme temperatures.
Method: In this paper, the approach has been used in the circulation to peripheral circulation patterns will be assessed based approach to environmental data. Therefore, we used two databases. First Base event database environment (surface). In this regard, the surface temperature is selected stations Kerman province. The maximum temperature of the stations in the period 01.01.1368 to 01.01.1398 for 30 years to 10957 the number of days were obtained from the meteorological province. Another database contains data that the data of geopotential height at 500 hPa

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This research study aims to investigate the effect of climatic variables, specifically precipitation, temperature, and humidity, on changes in vegetation indices of orange orchards in Hassan Abad, Darab County, using satellite data. Consequently, observational data, including orange tree phenology data and meteorological data from the agricultural weather station, were collected over a period of more than 10 years (2006 to 2016). MODIS images from 2006 to 2016 were referenced based on territorial data and 1:25000 maps from the Iran National Cartographic Center. These images were used to calculate remote sensing vegetation indices, namely the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). The results demonstrated that the variables of maximum humidity, minimum temperature, and precipitation have a significant positive effect on the NDVI variable. Additionally, the variables of maximum temperature and minimum humidity have a significant negative effect on both the NDVI and EVI. To determine the significance of each independent variable in predicting the dependent variables, the artificial neural network method was employed. The findings showed that the climatic elements of precipitation, minimum temperature, maximum temperature, minimum humidity, and maximum humidity had the greatest effect on EVI, with values of 0.39, 0.3, 0.13, 0.1, and 0.06 respectively. Moreover, the effect of these variables on the NDVI index is equal to their coefficients, which are 0.2, 0.28, 0.22, 0.11, and 0.17 respectively. Finally, the ARMAX regression method was used to improve the explanatory power of the model. The results indicated that this method enhanced the explanatory power of the model and reduced the forecasting error.

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Human interventions in natural areas as a change in land use have led to a domino effect of anomalies and then environmental hazards. These extensive and cumulative changes in land cover and land use have manifested themselves in the form of anomalies such as the formation of severe runoff, soil erosion, the spread of desertification, and salinization of the soil. The main purpose of this study is to reveal the temperature inductions of the land cover structure of Lorestan province and to analyze the effect of land use changes on the temperature structure of the province. In this regard, the data of land cover classes of MCD12Q2 composite product and ground temperature of MOD11A2 product of MODIS sensor were used. Also, in order to detect the temperature inductions of each land cover during the hot and cold seasons, cross-analysis matrix (CTM) technique was used. The results showed that in general in Lorestan province 5 cover classes including: forest lands, pastures, agricultural lands, constructed lands and barren lands could be detected. The results of cross-matrix analysis showed that in hot and cold seasons, forest cover (IGBP code 5) with a temperature of 48 ° C and urban and residential land cover (IGBP code 13) with a temperature of 16 ° C as the hottest land use, respectively. They count. In addition, it was observed that the thermal inductions of land cover in the warm season are minimized and there is no significant difference between the temperature structure of land cover classes; But in the cold season, the thermal impulses of land cover are more pronounced. The results of analysis of variance test showed that in the cold period of the year, unlike the warm period of the year, different land cover classes; Significantly (Sig = 0.026) has created different thermal impressions in the province. Scheffe's post hoc analysis indicated that this was the difference between rangeland cover classes and billet up cover.