ANALYSING TIME SERIES OF STANDARDIZED PRECIPITATION INDEX (SPI)
The Standardized Precipitation Index (SPI) is a simple and flexible tool for identifying dry and wet periods. This index does not depend on the geographical location, and can be applied at different time scales. The purpose of this work is to provide a statistical analysis of the time series of the one-month SPI indicator for the Rostov region for the period 1990-2020. To achieve this goal, the tasks of implementing a program for calculating SPI, forming a precipitation database, and evaluating the descriptive statistics of the time series of the index for the studied region were solved. This research contains statistical analysis of time series of the one-month SPI values for Rostov region over a period of 1990-2020. With the help of nonparametric method Mann-Kendall test statistically significant negative trends in dynamics of interannual standardized precipitation index volatility were identified. Taking into account the current trends of global climate change, the researched period was split into 3 terms, and, based on the results of descriptive statistics comparative analysis, the period of 2010-2020 appeared to be the doughtiest, but in 2020, the extreme drought was formed, caused by an anticyclonic weather regime. According to the volatility trends analysis, monthly SPI showed that the majority of tendencies identified do not pass the validation criterion (p-value ≤ 0.05), apart from August, when the fastest pace of the negative index changes from year to year was registered.