جستجوی مقالات مرتبط با کلیدواژه « extreme temperature » در نشریات گروه « جغرافیا »

The occurrence of heatwaves, even in short time periods, can disrupt daily life and many social activities for residents. This phenomenon, when it persists for longer durations, may cause environmental and agricultural damage. The objective of this research is to extract and introduce synoptic patterns that lead to the creation of heatwaves in the southern coastal cities over the past 33 years. To achieve this goal, using the Z-score index and other selected criteria, heatwave samples were extracted for all selected stations. Based on the selected criteria, 90 heatwave samples were extracted for the 33-year statistical period. Then, using the factor analysis method and visual inspection with 1000 hPa weather data, dominant and frequent synoptic patterns were extracted. The results of this research showed that seven factors and 14 frequent patterns are the most dominant synoptic patterns that create heatwaves during the cold season in southern Iranian cities. Among these patterns, the first factor of the Sudan-Turkmenistan low-pressure pattern and, among the effective systems in creating high heatwave temperatures, the Sudan low-pressure system had the most significant role in the structure of synoptic patterns. In this pattern, the Sudan low-pressure system is combined with a northeast expansion towards the South and the warm air movement of the Hadley cell, causing an abnormal rise in temperatures at coastal stations. The core heat of this pattern is located over Sudan and Saudi Arabia. In the boundary layer to the middle troposphere, the Arabian trough rotates over the region, creating dynamic

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.

Climate change is the greatest price society is paying for decades of environmental neglect. The impact of global warming is most visible in the rising threat of climate-related natural disasters. Globally, meteorological disasters more than doubled, from an average of forty-five events a year to almost 120 events a year (Vinod, 2017). Climate change refers to changes in the distributional properties of climate characteristics like temperature and precipitation that persist across decades (Field et al., 2014). Because precipitation is related to temperature, scientists often focus on changes in global temperature as an indicator of climate change. Valipour et al. (2021) reported the mean of monthly the global mean surface temperature (GMST) anomalies in 2000–2019 is 0.54 C higher than that in 1961–1990. Many studies have been done on climate change in Iran. These studies have mostly studied the mean and extreme temperature trends (Alijani et al., 2011; Masoudian and Darand, 2012). In general, the results of previous studies showed that the statistics of mean, maximum and minimum air temperature in most parts of the Iranian plateau have increased in recent decades. Also, the increase of minimum temperature is greater than maximum temperature. A review of the research background shows that we need to understand more about regional climate change in Iran. Therefore, present study performs the climate change of 14 extreme temperature indices using multivariate statistical methods at the regional scale.

Historical climate observations including daily maximum and minimum temperature were obtained from the Iranian Meteorology Organization for the period 1968 to 2017 at 39 stations. In this paper, 14 extreme temperature indices defined by ETCCDI were analyzed. The indices are as follows: (1) Annual maxima of daily maximum temperature (TXx); (2) Annual maxima of daily minimum temperature (TNx); (3) Annual minima of daily maximum temperature (TXn); (4) Annual minima of daily minimum temperature (TNn); (5) Cold nights (TN10p); (6) Cold days (TX10p); (7) Warm night (TN90p); (8) Warm day (TX90p); (9) Frost days (FD); (10) Icing days (ID); (11) Summer day (SU); (12) Tropical nights (TR); (13) The warm spell duration index (WSDI) and (14) the cold spell duration index (CSDI). The extreme temperature indices were extracted using R software environment, RclimDex extension. The Mann–Kendall Test and Sen’s Slope Method was employed to assess the trends in 14 extreme temperature indices. To identify homogeneous groups of stations with similar annual thermal regimes, Principal Component analysis (PCA) and Clustering (CL) was applied. Pearson correlation coefficient was used to investigate the relationship between height and trend slope.

All the extreme temperature intensity indices (TXx, TNx, TXn, and TNn) showed increasing trends during 1968 to 2017. The increasing trends of TXx, TNx, TXn, and TNn were 0.2, 0.3, 0.44, and 0.5 ° C per decade, respectively. These results indicated that the extreme warm events increased and the extreme cold events decreased. The average of the extreme temperature frequency indices over Iran showed that the frequency of warm night (TN90p) and warm day (TX90p) significantly increased with a rate of 6.9 and 4.2 day per decade, respectively. Also, the frequency of cold night (TN10p) and cold day (TX10p) significantly fell with a decrease rate of 3.8 and 3.8 day per decade, respectively. The frequency of warm nights (TN90p) was higher than that of warm days (TX90p). The result indicated that the trend of nighttime extremes were stronger than those for daytime extremes. The average of frost days (FD) and icing days (ID) indices over Iran showed decreasing trends during 1968 to 2017 with rates of 3 and 1.1 d per decade, respectively. While, the averaged of summer days (SU) and tropical days (TR) indices over Iran showed increasing trends with rates of 4.4 and 6.4 day per decade, respectively. The warm spell duration index (WSDI) indices showed a clear increase, with a rate of 2.1 per decade. In contrast the cold spell duration index (CSDI) showed a significant decrease, with a rate of 1.7 per decade. In general, the cold indices displayed decreasing trends, whereas the warm indices displayed increasing trends over most of Iran. Pearson correlation coefficient between height and Sen’s Slope was estimated to be equal to -0.62 (p < 0.01). In general, the results of this study showed that there is a negative correlation between the elevation factor and the Sen’s Slope of warm extreme indices. That is, as the altitude decreases, the Sen’s Slope increases. Therefore, the stations located in low altitude have experienced stronger increasing trends than in high altitude. The area of ​​Iran was classified into four clusters using PCA and CL methods. Cluster 1 has experienced the strongest increasing trends. The average height of cluster 1 is 535 meters. Approximately 38% of the studied stations were located in cluster 1. Cluster 2 showed a moderate heating trends. 33% of the stations were located in cluster 2. Most of the stations of cluster 2 are located in the northwest and west of Iran. Cluster 3 showed a weak increasing trends compared to clusters 1 and 2. The stations of cluster 3 did not show a special geographical concentration and were scattered in all parts of Iran. 18% of the studied stations are located in cluster 3. The stations of Cluster 4, have experienced weak decreasing trends, which was different from the other three clusters

In this study we analyzed the climate change of extreme temperature indices in Iran. The result showed that the frequency of warm nights, warm days, summer days and tropical days increased. Also, the frequency of cold nights, cold days, Frost days and icing days decreased. The warm spell duration index showed a clear increase. In contrast the cold spell duration index showed a significant decrease. In general, the extreme warm events increased and the extreme cold events decreased over most of Iran. There is a negative correlation between the elevation factor and the Sen’s Slope of extreme warm indices (R = -0.62). Therefore, the stations located in low altitude have experienced stronger increasing trends than in high altitude. The area of ​​Iran was classified into four clusters using PCA and CL methods. Cluster 1 has experienced the strongest increasing trends. The average height of cluster 1 is 535 meters. Therefore, the most heating have occurred in Low-lying areas of Iran. Cluster 2 and Cluster 3 showed a moderate and weak heating trends, respectively. The stations of Cluster 4, have not experienced clear trends.

Nowadays, cities are facing with increasing the urban heat island and reduction of the climate comfort Due to the urbanization and the reduction of urban green spaces. This research, therefore, aims to investigate green space reduction and its effects on relative humidity and temperature variability in Rasht, Iran during the period of 1964-2013. To do this, Landsat imagery, daily temperature extremes and relative humidity of the Rasht synoptic station were used. To measure the changes, NDVI, extreme temperature indices and Sen's slope estimator were applied. Results showed that the total green space in Rasht has fallen from about 7,255 hectares to 5,990 hectares and high density green space has dropped from 2855 hectares to 788 hectares. Also, DTR, ID, TN10p indices have been reduced with a 99% confidence. Whereas the indices of TR, TXx as well as TX90p with a confidence of 99%, and maximum relative humidity of Rasht with 95% confidence intervals are increased. Also, trends of the climate parameters are consistent with the green space reduction, and their trends have intensified over three consecutive decades. So that with the population doubling, the city's green space is reduced to about a third of the initial value and the indices such as DTR and FD decreased by about 4 ° C and 35 days, respectively. It seems that the increase of green space is necessary to reduce the effects of the urban heat island and the global warming for sustainable development. It should be taken into consideration in future planning.

The increase of earth temperature causes anomalies in the earth climate that this affair is itself affective on all the aspects of human life. In this context, the aim of this study was to consider the temperature changes and predict the extreme temperatures in Guilan and Mazandaran Provinces. The SDSM statistical and dynamical model is used and also for analyze the temperature changes and trends has been used the Mann-Kendal graphical and statistical technique. In this regard, the daily data of Rasht, Ramsar and Babolsar stations temperature were produced during the statistical period of 1961 to 2010 from Meteorological Organization and also the general circulation models data of HadCM3 and NCEP were taken of related database.The results revealed a significant positive trend in monthly and annual minimum and maximum temperature in all three stations in the first and third priod. Also in the second period, there is not a significant trend in extreme temperatures in Ramsar and maximum temperature in Rasht. The Mann-Kendal graphical test was done on the yearly extent temperatures of 3 periods and its results showed that by not reminding the critical border of 1/96 in the level of 95 percent assurance of changes of increase recess kind and also sudden changes has been occurred in all stations. In the forecast period, is seen the highest of changes in monthly and annual of the minimum temperature.The increase of extreme temperature was predicted about 0/1 to 1/7 centigrade. The short time oscillations and meaningful positive trend happenings in both of the maximum and minimum temperature shows the temperature increase in the future years that this indicates occurred climate changes.

High temperature extremes are a serious threat to society, the environment and the economics of countries. High extreme temperatures are important features of weather events. Human and natural physical caused climate change can affect climate extremes, as well as maximum temperatures. Heat waves and super-hot days occurrence was increased in recent years due to global warming phenomena. Since south east of Iran is in subtropical location, it is exposed to this extreme climate frequently. In the present study, statistical analysis and identification of synoptic pattern of extreme high temperature in south east of Iran were investigated. In order to do this, firstly temperature data of nine synoptic stations in south east of Iran were collected, and then Normalized Temperature Deviation output data were calculated and by using these data, summer days were categorized into hot, sever hot and super-hot days. Increasing of hot days was concluded. Twenty seven super-hot days were chosen for synoptic analysis. Gang thermal low pressure on earth surface and 850 HPa level and subtropical high pressure on two levels including 700 HPa and 500 HPa cause super-hot days. Ward cluster analysis shows no variation in these patterns. Advection of temperature on hot days shows that maximum temperature was occurred in south east of Iran and not originated from abroad.

Issue of climate change, global warming and the consequences tend to be the owners of the thoughts of statesmen and politicians around the world has attracted. To review the annual extreme temperature was used 42 years data from Shiraz synoptic station for the period 1971-2012. The global mean temperature anomalies data that ranged from 1990 to 2012 was used to examine the relationship between extreme temperatures and global warming. Statistical methods for linear regression and Man– Kendal were used for significant test for the trend of changes in the temperature series. Results indicate that despite the lack of long-term trend, after the onset of began the cold phenomenon, absolute minimum temperature gradient descending declining in Shiraz. Shiraz absolute annual maximum daily temperature is rising upward gradient, indicating a gradual increase in maximum temperatures and extreme heat of the summer.