Trends of Extreme Precipitation Events in Serbia Under the Global Warming

被引:0
作者
Tosic, Ivana [1 ]
da Silva, Antonio Samuel Alves [2 ]
Filipovic, Lazar [1 ]
Tosic, Milica [1 ]
Lazic, Irida [1 ]
Putnikovic, Suzana [1 ]
Stosic, Tatijana [2 ]
Stosic, Borko [2 ]
Djurdjevic, Vladimir [1 ]
机构
[1] Univ Belgrade, Fac Phys, Inst Meteorol, Belgrade 11000, Serbia
[2] Univ Fed Rural Pernambuco, Dept Estat & Informat, Rua Dom Manoel Medeiros S-N Dois Irmaos, BR-52171900 Recife, PE, Brazil
关键词
extreme precipitation events; trend; climate change; Serbia; DECADAL TRENDS; FUTURE CHANGES; TEMPERATURE; FREQUENCY; PATTERNS; INDEXES; EUROPE;
D O I
10.3390/atmos16040436
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This paper examines extreme precipitation events (EXPEs) and their trends based on daily precipitation values observed at 14 stations in Serbia for the period 1961-2020. The following EXPEs were investigated: RR10mm (heavy precipitation days), RR20mm (very heavy precipitation days), Rx1day (highest 1-day precipitation amount), Rx3day (highest 3-day precipitation amount), Rx5day (highest 5-day precipitation amount), R95p (very wet days) and R99p (extremely wet days). A positive trend for all EXPEs was dominant in Serbia from 1961 to 2020. All annual Rx1day time series show a positive trend, which is significant at 12 out of 14 stations. The highest values of all EXPEs were observed in 2014, when the annual precipitation totals were the highest at almost all stations in Serbia. To examine the potential influence of global warming, the mean values of the EXPEs were calculated for two periods: 1961-1990 and 1991-2020. In the second period, higher values were determined for all EXPEs than in the first period. The large-scale variability modes, such as the North Atlantic Oscillation (NAO), the East Atlantic Oscillation (EA), and the East Atlantic-West Russia (EAWR) pattern, were correlated with the EXPEs. A negative correlation was found between the EXPEs and the NAO and the EAWR, and a positive correlation between the EXPEs and the EA pattern. For future research, the contribution of high-resolution data will be examined.
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页数:18
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