Spatio‐temporal changes in the mean and extreme temperature indices for Serbia

Abstract

AbstractThis study provides a comprehensive analysis of changes in mean and extreme temperature indices for Serbia using a high‐resolution daily gridded temperature data set during the period of 1951–2020. The annual and seasonal trends of the indices in the gridded fields were computed and tested for statistical significance using the nonparametric Mann–Kendall test and the Sen's slope estimator. The t‐test was applied to check the stability of means of temperature indices between two standard periods (1961–1990 and 1991–2020). A correlation analysis was used in order to investigate the connections of the large‐scale circulation patterns and the mean and extreme temperature indices. Results showed that a warming trend dominated for the last 70 years, with slightly more intense changes for the mean maximum temperatures (TXM) than for the mean minimum temperatures (TNM). An increase was recorded for indices based on the maximum temperature (TXM, hottest days, warm days, summer days) and minimum temperature (TNM, coldest nights, warm nights, tropical nights). The highest increase was observed for warm nights (7 days⋅decade−1) during the summer season. The negative change in cool days (−1.5 days⋅decade−1) and cool nights (−2 days⋅decade−1) was recorded in almost all seasons, being significant for the both annual and summer values. The correlation between the temperature indices and large‐scale circulation patterns revealed that the East Atlantic (EA) pattern had a highly positive correlation with warm temperature indices (hottest days, warm days, warm nights, summer days, and tropical nights) and a negative correlation with cold indices (coldest nights, cool days, cool nights, frost days, and ice days). The North Atlantic Oscillation, the most important teleconnection pattern during the winter months in Europe, had weaker influence on temperature indices in Serbia than the EA pattern, but stronger than the EA/Western Russia pattern.