جستجوی مقالات مرتبط با کلیدواژه « دمای حداقل » در نشریات گروه « جغرافیا »

The purpose of this study is to investigate the temperature limit indices in Kermanshah province. For this purpose, daily temperature data of 19 synoptic stations from its establishment until 2018 and extreme temperature indices have been used. Studies have shown that glacial indices (IC) and cold waves (CW) have the highest correlation with other indices. Therefore, the mentioned indicators were considered as representative indicators and the trend and also the pattern of spatial autocorrelation were studied for these indicators. The I - Kendall method was used to examine the trend and the spatial index G * was used for the spatial autocorrelation model. The results showed that the glacial index in the eastern highlands has a maximum frequency for 1 to 6 days and has an increasing trend in the lowlands of the southwest. The cold wave index is also the most frequent in the eastern regions in all continuities and shows an increasing trend in parts of the province. The results of spatial autocorrelation pattern of G * index showed that the positive spatial autocorrelation pattern of cold and ice waves has been observed more in the eastern highlands of the province. The pattern of negative spatial autocorrelation is mostly formed in the western half of the province, i.e., the border areas of Iraq, which indicates the role of the Zagros elevation distribution in the formation of the glacial autocorrelation pattern in the province.

Temperature is one of the most important elements in weather and climate forecasting. Therefore studying temperature behavior is important for understanding climate variability that can vary at different spatial and time intervals and local, regional and global scale. The International Climate Change Board (IPCC) has clearly indicated that global temperature trends have increased by about 0.85 ° Cover the period 1880 to 2012. Climate change usually has enormous impacts on people and their temperament, agricultural resources and access to water, especially in areas where their economic activity is dependent on agriculture (as in most parts of Iran). Iran's climate is diverse due to the complexity of the topographic features and the vast geographical extent. Therefore, the effect of major local factors on climate change must be identified.These results can help confirm the studies of climate models that this also helps in planning for agriculture and water supply, especially for the future. In previous decades, most temperature analyzes focused on average values. In recent year's low-temperature analysis has broadly focused on Changes in the occurrence of extreme temperatures with high frequency, Number of days over different temperature limits, Regional trend of minimum and maximum temperatures and diurnal temperature difference events.

This article evaluates the monthly mean and seasonal Minimum and maximum temperature variability in autumn (October-December), winter (January-March) and also the cold period (October-March over a 60-year (1951-2010) statistical period. Stations with 60-year statistics included 26 cases. Before using the data, it is synchronized and any possible errors are removed. Changes in mean and variance were tested by conventional methods. Statistical processing was performed using R software. According to World Meteorological Organization methods, Required statistics include mean, coefficient of variation, probability of up and down 20%, standard deviation, daily and monthly temperature and minimum and maximum temperatures in two 30-year(1951-1980),(1981-2010) and 60-year(1951-2010) periods were calculated. Then, using the Mann-Kendall test, the trend of this minimum and maximum temperature over a 60-year period was determined. The patterns of each statistic are plotted and interpreted using the

The results show that the lowest mean temperatures are in the fall, winter, and cold periods in the northwest and north regions and the lowest is in the south and southeast of the country. The lowest coefficients of change in minimum temperatures for autumn, winter, and cold periods are the northern and southern coasts and the eastern and southeastern parts of the country and the southern and central coasts of the country respectively. The highest coefficient of variation is winter in Hamadan and Gorgan and in cold period in Gorgan and Rasht. In the autumn, the coefficient of variation is generally low. In addition, the lowest maximum temperatures occurred in autumn in the northwest and west and in winter in the north and northwest, which coincided with the pattern of maximum coefficient of variation. The years with a high frequency of 20% at the stations under study are synchronized at both minimum and maximum temperatures. But for the 20% lower limit, this coordination is not seen only in the first 30 years of autumn. Also in the last decade compared to the first decade the minimum temperatures during the autumn, winter and cold periods decreased at 8, 4 and 7 stations and at 18, 22 and 19 stations have increased respectively. In the fall, the maximum temperature only declined at three stations, and in the other two periods, all stations showed an increasing trend and the results in a decrease in the diurnal temperature difference.

Most of the minimum temperature variability is in the northwest and west and northeast of the country that the reason could be the arrival of different air masses, especially through the northwest and west of the country. But on the north and south coasts of the country, this variability is less due to the moderating effect of the sea. Also, the variability in autumn was higher than winter, which it shows the most active air masses in the winter. The occurrence of the highest maximum temperatures in the southern regions with the lowest coefficient of variation indicates a more uniform temperature conditions than elsewhere. Also, in most parts of the country, the diurnal temperature difference has decreased..

Average surface temperatures of the Northern Hemisphere have risen in response to climate change by 0.76°C over the past 150 years (IPCC, 2007) .These temperature increases have been accompanied by a reduction in snow and ice cover, retreat of sea ice and mountain glaciers, a longer growing season and earlier arrival of spring, increased frequency of extreme rainfall events, and more than 25,000 other changes in physical and biological indicators of global warming (Rosenzweig et al., 2008). Numerical models have used in such research after the late of year 1970s. The downscaling software such as SDSM,LARS_WG and ANN (Artificial Neural Network) became very common in the recent decades(e.g. Khan, et al., 2006).The results have showed that the SDSM is the most capable of reproducing various statistical characteristics of observed data in its downscaled results with 95% confidence level, the ANN is the least capable in this respect, and the LARS-WG is in between SDSM and ANN. According to Lopes et al (2008) in Assessment of climate change in Lisbon, the SDSM tool was able to better represent the minimum and maximum temperature whereas LARS-WG simulations is slightly better for precipitation.
Material and This research has used downscaled methods for the minimum and maximum temperatures of five stations including Anzali, Rasht, Babolsar, Ramsar and Gorgan in the southern coastal of the Caspian sea by three models namely LARS-WG, SDSM and ANN during 1961-90 and 2010-2039 period under three scenarios of A1 , A2 , And B2 . For this purpose, first the observed data of 1961-90 period were obtained from Meteorological Organization of Iran. Since GCMs are restricted in their usefulness for local impact studies with their coarse spatial resolution (typically 50,000 km2) and inability to resolve important sub–grid scale features such as clouds and topography, the three downscaling models namely SDSM, LARS_WG and ANN were used to downscaling these coarse data. Two GCM data were obtained from the website: http://www.cics.uvic.ca/scenarios/index.cgi?Scenarios. Root Mean square error (RMSE), Mean absolute error (MAE) and Coefficient of determination ( ) were used to assessing the capability of the models.
Result and SDSM model results showed very small error ( 0.01 to 0.06°C) between observed and generate data using NCEP predictors-based data with a little more discrepancy using HADCM3 predictors-based data . The model output showed minimum and maximum temperature will rise during the future period with the exception of the months including April ,May and November. This warming trend was same for ANN with error range of 0.2 to 0.8°C. LARS-WG simulation showed temperature will rise for all months of the year with the error range of 0.1 to 0.2°C. The comparison betweem three models showed that the SDSM tool was able to better represent the minimum and maximum temperature.
According to this study the temperature increased during the target period. Temperature will increase during future period too.The SDSM and ANN model showed decrease in the temperature of the months including April, May and November. But the LARS_WG showed increase in the temperature in all month and all stations. The comparison of the models showed that the SDSM model has recorded the lowest error in the predicting of future temperatures.

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 with47219 cases from 350 stations and the month of Aban with 17728 cases from 305stations, had the highest and the lowest frequency of occurrence.

In this study, linking between the North Sea–Caspian Pattern (NCP) and minimum temperatures fluctuation in Iran for 60 years period (1950-2010) has been investigated. The data used in this study included monthly temperature data from 17 synoptic stations in different regions of Iran, the NCP index data and upper atmospheric reanalysis data (geopotential height, zonal wind, meridional wind, temperature and thickness (1000-500 Hpa)). Pearson correlation analysis as the main method was used in this study and showed an inverse significant relationship between minimum temperatures in most selected stations and NCP index. This proves a decrease of temperature in positive phase of the NCP and increase of minimum temperature in negative phase. In terms of temporal analysis, there was a significant negative correlation between the minimum temperatures of stations and the NCP in months of January, March and February. In between stations, the monthly highest calculated correlation with -0.349 (=0.01) was computed in January. Calculated seasonal correlations show that the highest significant correlation between NCP and minimum temperatures is for winter with -0.237 (=0.01). From periodical perspective, the results indicate a strong correlation between cold period and NCP in most stations. Zahedan station had the weakest correlation with the NCP. This is probably due to its remoteness from active centers of NCP. Atmospheric patterns in 500 Hpa level in positive and negative phases of positive phase, prove the settlement of a deep trough on the Caspian Sea, Iraq, Turkey and Iran, and also the location of Iran in the eastern part of the trough axis and on the other hand, the settlement of a deep ridge on the North Sea and Europe led to the advections of cold temperature from Northern Europe near polar regions in Arctic to Iran. In negative phase placement of the study area beneath the ridge axis, led to the creation of a barotropic atmosphere with weak zonal wind and advections of warm temperatures to Iran. Therefore, with advections of warm temperatures from Africa, Arabian Pennsylvania and low latitudes, temperatures rise in Iran.

Today one of the most important problems in Agriclimatology in effecting of climate on products. One of the climate elements in freezing which according to the continuity، extend and amount of it on agricultural activities، transportation and invironment has a lot of affections. Least temperature forcasts as one of the important climatic elements to forcasting late coldness and freezing in spring is very important. One of the new ways in forcasting climate elements is Artifical Neural Networks (ANNs). For this purpose from a 27 periodical time (1986-2012) Synoptical station in zab baisn inMatlab software for aducating and testing the topic has been used. The best model for Artifical Neural Network to forcasting least temperature is Presptron with 3layers and 5 Nerons in interal layer، 4Nerons in hidden layer and one Neron in output layer and Marqwart-Lonberg Algoritm.

This article was conducted in order to gain more knowledge about thermal differences (Thermal Island) between Tehran and Karaj based on a five-year statistical period (1993-1997). The element of temperature as the most important climatic element has been obtained as daily minimum and maximum from the Meteorological Organization of Iran. In the study of thermal island, stations of Dushan Tappeh in the east, Aqdasieh in the north and Mehrabad in west of Tehran, as the most important study area and Karaj station in west of Tehran as complementary area, have been selected. Based on the investigations carried out on the average temperatures of three stations in Tehran and Karaj station, it was observed that Dushan Tappeh as the most important thermal region in Tehran has the highest temperature values ​​for both minimum and maximum annual temperatures with temperatures 13.33 and 22.49 ° C, respectively. Next, Mehrabad station has been determined as the second thermal zone in Tehran with the minimum annual temperature of 12.88 ° C and 12.29 ° C at maximum temperatures. Third, Aqdasieh station, with a mountainous character and higher elevation than the rest, acts as a relatively weak thermal zone, the average annual minimum temperature at this station being 10.33 and the maximum temperature 19.9 ° C. Generally, the mean annual temperatures of all three stations in Tehran have higher temperature values ​​at both minimum and maximum temperatures than Karaj station, so that Tehran has a temperature difference of more than 0.75 ° C in the mean annual maximum temperature and a temperature difference of 3.37 ° C at the average annual minimum temperature with Karaj, and so has been recognized as the warmer region.

In this research, first the concepts of the climate changes phenomenon are investigated regarding to their statistical features. Also for better understanding of the concepts of the climate changes phenomenon, it s been analyzed minimum and maximum absolute temperature and temperature mean of Rasht station. For achieving this aim, we collected a forty¬¬¬¬-eight year information(1956-2003) of the above mentioned station, next using some statistical analyses and determining equations with applying Spss and Excel software, it has been demonstrated that the rate of the minimum absolute temperature has been increased during four seasons and the temperature mean and absolute minimum in the early of the period(up to 1980) is less than 1980 to 2003.The seasonal graphs of the minimum absolute temperature show that the fluctuation of the minimum absolute temperature in seasons has been decreased from the first periods(1956-1980) to the second periods(1980-2003) also the intensity of the minimum absolute temperature has been reduced and the minimum absolute temperature include on increasing procedure. It s been predicted that the minimum absolute temperature of Rasht station will be increased in spring (5.47), summer(5.6), fall(5.02) and winter (2.75) than the early of the period. Climatically time displacing is being clear within seasons and the cultivated calendar is changing.

Investigating slope instability and determining areas prone to slope movements bymeans of GIS has been considered by researchers in the past recent years; however,sufficient attention has not been given to the methods employed in GIS.The present article uses a cell analysis method in a slope instability studyconducted at Sanandaj Country, and has obtained an appropriate model fordetermining prone areas. While testing the model, the cell analysis method has beencapable of assessing the factors influencing slope instability and creating modificationchanges in weights and coefficients.