Analysis of the Trend of Changes in Some Synoptic Parameters Using Quantile Regression in Babolsar

Climatic events such as floods, storms and droughts are often caused by extreme weather. Therefore, it is important to study the trend of different ranges of climatic data rather than just average. Most trend detection studies are based on the analysis of changes in mean data and do not provide information on how changes occur in different ranges of the used data range. Therefore, to investigate the trend of changes in different ranges of the time series of climatic data, quantile regression method was proposed. The quantile regression has the ability to examine the changes trend in different quantiles of the data series. Therefore, in this study, we was analyzed the changes trend in the different quantiles of temperature minimum and maximum, precipitation and maximum daily wind speed data time series in Babolsar synoptic station for a period of 62 years (1959- 2020) seasonally and annually. The results showed that the minimum and maximum temperature and wind speed increased significantly in all seasons. The intensity of these increasing trend was higher in the extreme lower quantiles of the daily minimum temperature and extreme upper quantiles of daily maximum temperature in winter. But the wind speed data, in the upper quantiles especially extreme upper quantiles have increased to a much greater intensity than the lower quantiles, especially in autumn. The precipitation did not change significantly in the 62-year period. On an annual scale, the maximum increase for the minimum and maximum temperatures was in the extreme lower quantiles 4.28 and 2.85 degrees centigrade, respectively, and for the wind speed, it was in the extreme upper quantiles 8.24 meters per second.