Air conditioning systems are used in industries and residential environments with the aim of improving environmental conditions and creating a comfortable temperature for users. Considering the production of sound and vibration in most of its components, the lack of control of the production sound level always exposes the users to unwanted sound, which in addition to hearing complications, also causes fatigue and dissatisfaction with the environmental conditions. . Compressors are one of the most important sources of sound production in air conditioning systems, and screw compressors are one of the most widely used in air conditioning industries. Therefore, the compressor shell should be designed to minimize the transmission of sound from inside to outside. Since the maximum working temperature of compressors is up to 80 degrees Celsius, therefore, in this research, an acoustic test was performed on a sample of a screw compressor shell in two modes of ambient temperature and maximum working temperature inside the acoustic room, and the effect of temperature increase on the sound pressure level. transferred from the shell to the external environment is discussed. Finally, based on the frequency analysis performed in two conditions of ambient temperature and maximum working temperature and comparing the amount of sound transmitted to the environment at different frequencies, practical solutions to reduce the amount of transmitted sound pressure have been presented.

Due to the importance of meteorological data and limitations of data gathering from ground stations, remote sensing can play an important role in the preparation of these data. The purpose of this study was to quantitatively evaluate the Land Surface Temperature (LST) obtained from Moderate Resolution Imaging Spectroradiometer (MODIS) sensor images for estimating the maximum and minimum daily air temperature in the Taleghan watershed. For this purpose, the maximum and minimum daily air temperature data of three existing ground stations for the period 2009 to 2015 were obtained. Day and night LST and Normalized Difference Vegetation Index (NDVI) values ​​of MODIS were also prepared. The relationships between each of the effective variables and maximum and minimum daily air temperature in ground stations have been extracted using multiple linear regression method. The results showed that there was a significant correlation between maximum and minimum daily temperature of ground stations with day and night LST and NDVI from MODIS sensor. Therefore, these variables were used in regression relationships. The results of validation showed that the established relationships with all effective variables had the most accuracy. Therefore, the best model for estimating the maximum daily air temperature had , NSE and RMSE values ​​of 0.74, 0.74, and +4.7, respectively and for estimating the minimum daily air temperature had 0.71, 0.72 and +2.9, respectively. Therefore, by converting the surface temperature obtained from MODIS sensor images, the air temperature can be estimated with high accuracy on a daily and monthly scales for various studies.

Investigation of the Temporal and Spatial Variation of Maximum Soil Temperature in Iran Extended Abstract Introduction The study of soil temperature in different depths of soil is important in climatology, hydrology, agrometeorology and water resource management. Different depths has a different temporal and spatial soil temperature variation. It represents the regional ground temperature regime. Furthermore, due to its rapid response to environmental changes, soil temperature is one of the most important indicators of climate change. The increase in soil temperature because of global warming can promotes disasters such as drought by increasing the water demand of agricultural products during the plant growth period. The increase in soil temperature also have a various consequences, include increasing evaporation from the soil surface, soil salinity in susceptible areas, which can lead to a decrease in soil yield and failure in plant growth. Therefore, knowledge of soil temperature changes in different environments is very important in climate studies. The aim of the current research is to analyze the spatial and temporal variations of soil temperature at different depths from five to 30cm of the ground and to investigate the existence of any kind of increasing or decreasing trend at different climates of Iran. Methodology Hourly soil temperature data (depths of 5, 10, 20 and 30 cm) were used in this research for the period of 1998-2017. The soil depth temperature is measured three times a day at 6: 30 am, 12: 30 pm, and 6: 30 pm local time (3, 9, and 3 p. m. UTC). These data have been received for 150 synoptic stations of Iran on a daily basis from the Iran Meteorological Organization (IRIMO). IRIMO monitored the quality of soil temperature for data entry, data recording, and data reformatting errors. Data availability, discrepancies, errors, and outliers were identified during the second stage. At the first step, temporal coefficient of variation were calculated for available soil temperature time series from five to 30 cm depths of each station. For this purpose, the average of three daily measurements of soil temperature was calculated and then the temporal coefficient of variation was obtained. In the next step, trend analysis of soil temperature has been investigated using the non-parametric Mann-Kendal test. The trend slope was calculated using Sen’s slope for each station in seasonal time scale. Trend analysis has been done for all three observations of the day. Results and Discussion The studied stations show significant spatial patterns in the temporal variability of soil temperature. In all four investigated depths, from five to 30 cm, the northwest parts of Iran, and some parts of Zagros and Alborz mountain ranges have high temporal coefficient of variation. In contrast, the stations located on the southern coasts and southern islands had the lowest temporal variability. In warm and cold seasons (summer and late autumn to mid-winter), the spatial changes of soil temperature at different depths are lower than spring and early autumn. However, in the warm period of the year, the soil temperature experiences lower spatial variations at different depths. Spring and autumn seasons, as the transition period from cold to warm and warm to cold seasons, show the most spatial temperature variations in Iran. Detected trends do not have significant differences among the three observations of the day. Soil temperature Trend analysis at different depths showed positive values for two seasons of summer and winter over most of the stations throughout Iran. Extreme trends are more frequent in the summertime of Zagros and Alborz mountainous regions, while in the winter season the stations located at the southern latitudes of Iran have experienced the most positive trends. In the summer season, higher trends with 99% confidence are more frequent in the mountainous areas. These positive trends in soil temperature have occurred in all studied depths. The negative trend at different depths is a distinct feature of the autumn season, which is significantly more prevalent than other seasons throughout Iran. The analysis of soil temperature trends in different depths shows that values above 1 degree Celsius often occur in 5 to 20 cm deeps. The increasing trend of soil temperature in winter shows a greater spatial expansion, which is indicate increasing annual minimum soil temperatures and the increasing trend of Iran's soil temperature. Keywords: Soil Temperature, Spatiotemporal Variations, Man-Kendal Test, Sen's Slope, Iran

Temperature leaves undeniable effects on human activities and natural processes. The analysis of average maximum temperature and the highest temperatures related to the heat wave phenomenon is of great importance. The most important goals of this study include the investigation of the geographical distribution of the maximum average temperatures and extreme temperatures based on the time series and the gathered trends, changes, and differences with regard to the ripples and geographical latitude. Average maximum temperatures and the highest temperatures are the temperature variables that their increase or decrease affects the related decisions and the short-term and long-term planning in agriculture, architecture and urban development, Industry, and Labor. This study investigates maximum temperatures of Iran between 2005-1966, then, it offers the time changes and geographical patterns in the form of zoning patterns.

The global warming process during last century has not only affected on amount of atmospheric parameters but also affected on onset and end of each atmospheric parameters. The air temperature trend has been increasing during recent decades, especially in the regions such as Iran which is located in dry and semi-dry world belt. In this investigation, using Mann – Kendall statistical test, which is one of the proposed methods of World Meteorological Organization (WMO) for time series analysis, the trend of seasonal maximum and minimum temperatures in Iran will be studied. Hence, In this research, the daily data of maximum and minimum temperature with spatial resolution of 0.5 *0.5 degree received from cell database in the world scale, available in data base: http: //hydro.engr.scu.edu/files/, and converted to utilizable file (.TXT) in mat lab software by using Grads software. In continuation, Mann-Kendall script code, executed for a 21550*2058 matrix to calculating the threshold trend of 95% in Mat lab. We use from Arc GIS software for graphical representation of results. The results of this research indicate that the maximum temperature of northwest and southeast of Iran is without trend (trendless) in every four seasons, and in the winter, north-eastern of Iran have the least area. In the autumn, the increasing trend of maximum temperature seem more in the eastern area and Fars, whereas, the maximum temperature of autumn in without trend (trendless) in central and northwest area of Iran. The minimum temperature has increasing trend in the most regions of Iran. In this relation, the increasing trend of minimum temperature in winter is completely obvious in northwest, Zagros and southeast of Iran.

One of the ways to reconstruction of climatic variables, especially temperature, is dendroclimatology or the use of tree-ring width chronology. There did not so far exist any tree-ring based reconstruction of long term temperature in Caspian Ecosystem. Throughout the present research, temperature was reconstructed using Fagus Orientalis tree-ring chronology samples collected from high elevated regions of Koliak (Nowshahr). To follow the target, a correlation between annual tree ring width and meteorological variables in local and as well in global scales was considered. Correlation analysis revealed that drop in maximum temperature is a limiting factor of tree growth, particularly in the period March-September. So, the average of March-September maximum temperature (based on data taken from Nowshahr’s station) was reconstructed. The results of temperature reconstruction showed that this region has experienced very cold years more than it has very warm ones within the past two centuries. Also the first decade of 20th century and years, 1950-1970 vs the decade of 1830th, and years 1930-1950 formed the warmest vs coldest periods, respectively. Besides, the significant effect of negative NAO on temperature rise in the early months of growth period was revealed. Reconstructed temperatures of this research as like the results obtained by other researchers in Eastern Mediterranean didn’t show any warming trend within recent years.

Temperature is one of the important elements of weather, resulting in part from solar energy absorbed by the effects of the Earth's surface and is converted to thermal energy. Maximum temperatures in the hot period of the year, especially in the hours after the city, should be given more attention. Analyzing the maximum temperature can also be normal evaluation mechanism to evaluate changes and track climate change. This study aimed to identify the spatio-temporal patterns and determine the maximum monthly patches of country, so the main focus of the maximum temperature will be identified...

Soil temperature is an important physical parameter that affects energy balance between the atmosphere and earth’s surface. Soil and air temperature which are controlled by surface energy balance, have strong physical relationship. Because of the difference in thermal capacity between air and soil temperature, lag time exists between the occurrences of maximum of soil (Ts) and air (Ta) temperatures. In this research, observed daily soil temperature (6 depths) and screen temperature (170 cm) data were used from 1993 to 2008 for different climates including: Ahvaz (arid), Tabriz (semi-arid), Ilam (Mediterranean), Babolsar (humid) and Rasht (hyperhumid). Since, there are limited studies which have investigated the lag-time between the occurrence of maximum soil temperature (Ts) and screen temperature (Ta), this study aims to investigate the role of the lag-time on annual Ts-Ta regression relations. We constructed various regression equations between maxima of Ts (at 50 and 100 m) and Ta (170 cm). Using correlation method and Fourier series approach, the time lag between Ts (independent variable) and Ta (dependent variable) was also determined for all the study sites. Results from the mentioned methods were compared by RMSE, MAE, MBE and MPE criteria against each other. The differences between the two methods were statistically insignificant. The numbers of lag days (NLD) were found to be nearly the same for either mentioned methods. Regression equations between two statistical pairs (Ts-Ta) were constructed for two different scenarios (with and without lag) and the corresponding coefficients of determination were compared for the above scenarios. Results revealed that inclusion of NLD could significantly improve the Ts-Ta regression equations (at P<0.1 significant level), in particular for 100 cm depth. In addition, the NLD and the.