Özet:

Understanding the long-term variations of extreme temperature events is important for detecting and understanding the characteristics of climate change. However, it is not clear to what degree urbanization impacts climate change. In the study, station pairs were created by selecting 42 stations that recorded data between 1970-2018 to reflect the climate characteristics seen in Turkey. The changes of the selected climate indices in these station pairs in the hot (April-September) and cold (October-March) periods were examined by taking into account the observations covering the years 1970-2018. This study utilized the RClimDex program and Mann Kendall trend analysis technique. The RClimDex program was used to generate 27 climate indices. The information derived from the indices not only demonstrates how the mean value changes over time, rather, it; also contains information about how the statistical distribution of the data has changed. In addition, the results provide crucial information about the trends of extremes. In the study, 4 indices related to temperature (Diurnal Temperature Range, Cool Nights, Warm Nights, Minimum of Minimum) were selected and examined. When the changes in the climate indices of the selected stations in the hot and cold periods are examined, it is observed that the change in the hot period is more pronounced than the change in the cold period. According to Mann Kendall trend analysis, most of the trends are statistically significant at the 95% level in all station pairs examined. Results of the trend analysis show that the fastest tendency to increase occur in stations located in the Black Sea, Aegean and Mediterranean coastal zones where the moisture content in the air is higher. This finding points to the positive feedback mechanism created by the increased moisture content in atmosphere through global climate change.

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