Evaluation of time series of Tunceli climate parameters with different statistical analysis methods

Abstract

One of the most challenging environmental problems facing the world society today is climate change. The negative effects of climate change on human and natural systems are increasing. To understand the effects of climate change, trends in climate data need to be studied extensively. However, the contribution of climate observations made on a global scale to planning made at local and regional scales is low. Therefore, local climate analyzes are required to evaluate and develop strategies to minimize the harmful effects of climate change. Tunceli is located in a sensitive area against climate change. The aim of this study is to explain the long-term trend analysis of the climate parameters of the Tunceli meteorological station, which is located in an area sensitive to climate change, and the relations of the parameters with each other. In the study, 5 different statistical analysis methods were applied to the long-term time series of 15 parameters. First of all, Buishand homogeneity test was applied to each time series in order to question whether the time series of climate parameters are homogeneous and to determine the change point in non-homogeneous data sets. Secondly, Mann-Kendall and Şen's innovative trend analysis methods were applied to the time series to determine if there is any trend. The results obtained from the Mann-Kendall trend analysis and Şen innovative trend analysis method were compared and the consistency of the trend determined in the parameters was tested. Fourth, the regression analysis method was applied to the time series of climate parameters. With the regression analysis, the annual average change and long-term averages and rates were determined in each time series. Finally, the relations of the parameters with each other were questioned by the correlation analysis method and the severity and direction of the relationship was tried to be explained in the light of the available data. According to the common results of the analyzes, the increase in the maximum temperature, minimum temperature, average temperature and number of foggy days in Tunceli; A decrease in the values of total precipitation, number of rainy days, maximum relative humidity, average wind speed and number of days with snow was detected. The results of the analysis show that there may be serious drought and water insufficiency problems that may be caused by drought in the near future in Tunceli.