Ranking of multi-day extreme precipitation events over the Iberian Peninsula

被引:26
|
作者
Ramos, Alexandre M. [1 ]
Trigo, Ricardo M. [1 ]
Liberato, Margarida L. R. [1 ,2 ]
机构
[1] Univ Lisbon, Fac Ciencias, Inst Dom Luiz, Edf C8,Piso 3,Sala 8-3-1, P-1749016 Lisbon, Portugal
[2] Univ Tros Os Montes & Alto Douro, Escola Ciencias & Tecnol, Dept Engn, Vila Real, Portugal
关键词
Iberian Peninsula; accumulated precipitation; ranking events; high-resolution dataset; LARGE-SCALE DYNAMICS; LISBON REGION; RAINFALL; IDENTIFICATION; CLIMATOLOGY; LANDSLIDES; PORTUGAL; IMPACTS; DROUGHT;
D O I
10.1002/joc.4726
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
An objective method for ranking extreme precipitation episodes in different time scales over the Iberian Peninsula (IP) is presented. It relies on the extensive use of the high-resolution (0.2 degrees) gridded daily precipitation database available for the IP, spanning from 1950 to 2008. The sum of the normalized anomalies is computed over different time scales (2-10 days) to allow ranking the different anomalous precipitation multi-day periods. The magnitude of a precipitation episode is given taking into account the area (in percentage) that has precipitation anomalies above two standard deviations (std) and the mean values of these anomalies over this area. With these criteria, we are able to evaluate the spatial extent of the precipitation episodes as well as their spatially integrated intensity. Different precipitation rankings are built for the entire IP, for Portugal and independently for six of the major river basins in the IP. The different rankings correctly detect and categorize the most extreme precipitation episodes which occurred on the various domains. For each domain, in general, results show that few events dominate the top ten of a particular ranking; specific extreme events at shorter time scales (e.g. 2-3 days) may be absent from the top rankings at longer time scales (e.g. 10 days). When comparing the different domains, the top ten events are generally different from each other, thus highlighting the spatial variability of extreme precipitation in the IP. Moreover the methodology used to build the rankings imply that some events are considered extreme due to particularly high precipitation totals, while other episodes are more dependent on extensive areas affected by less extreme precipitation values. The different rankings revealed to be an useful tool for future studies in identifying the meteorological impacts of extreme precipitation episodes at the regional scale covering relatively large areas.
引用
收藏
页码:607 / 620
页数:14
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