Identification of Small and Large Fluctuations of the Daily Rainfall Time Series of Poldokhtar

Precipitation is considered as the most important factor in shaping the state of climate and the change of water on the surface of the earth, the surface of the soil and the atmosphere. fluctuating and multiscale signal appears, which has strong local fluctuations. In this study, in order to detect extreme large and small fluctuations in the daily precipitation time series of Poldokhtar synoptic station, two approaches of multifractal analysis of detrended fluctuations (MF-DFA) and discrete wavelet analysis with maximum overlap (MODWT) were used. The results of the analysis of annual fluctuations, two, four, eight and 12 years indicate the existence of three fluctuation periods in the precipitation signal for the annual scale. So that the fluctuations in the first period have a relatively regular behavior with a constant trend, in the second period they have a decreasing trend and finally in the third period they have an increasing and highly fluctuating trend. Extreme large fluctuations have a maximum in 2018-2019 and extreme small fluctuations have a maximum in 2011. Also, the results of the analysis of fluctuations in the time scales of one to 12 years show a decrease in extreme small fluctuations and an increase in extreme large fluctuations, and in the periods when there was an increase in precipitation, there was an intense increase in large fluctuations and the periods that were parallel to an intense decrease in precipitation, extreme small fluctuations also show an intense increase.