Analysis of drought in the region of Abruzzo (Central Italy) by the Standardized Precipitation Index

被引:42
|
作者
Di Lena, B. [1 ]
Vergni, L. [2 ]
Antenucci, F. [1 ]
Todisco, F. [2 ]
Mannocchi, F. [2 ]
机构
[1] Reg Abruzzo, Agr Polit & Rural Dev Management, I-65127 Pescara, Italy
[2] Univ Perugia, Dept Civil & Environm Engn, I-06121 Perugia, Italy
关键词
CLIMATE-CHANGE; RAINFALL TRENDS; VARIABILITY; 20TH-CENTURY; CALABRIA; IMPACT; SCALE;
D O I
10.1007/s00704-013-0876-2
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
The paper presents a comprehensive analysis of drought phenomena in the Region of Abruzzo (Central Italy) using the Standardized Precipitation Index (SPI) computed at different time scales (3, 6, 12, 24 months). The study is based on monthly precipitation data collected from 1951 to 2009 at 69 climatic stations uniformly distributed over the region. According to the trend analysis, most stations are characterized by increments in both drought severity and variability, particularly at the longer time scales. A principal component analysis applied to SPI time series enabled to identify two main patterns: the first more correlated to the coastal areas, the second more correlated to the inland, mountainous areas. However, the spatial patterns become less defined as the time scale increases, making more uncertain the definition of homogenous areas to be used in drought management plans. In most cases, the identified drought patterns have similar negative overall tendencies, but different trend directions in some sub-periods. In particular, the first drought pattern is clearly characterized by a trend reversal (from decreasing to increasing) during the last decade. This temporal evolution, consistent with that observed by large-scale analyses in the corresponding (or near) grid points, was not detected for the second pattern, which is probably influenced by local topographic and/or orographic factors. The results confirm the complexity of drought phenomenon in a typical Mediterranean region and the necessity of high-resolution datasets to capture its temporal and spatial variability.
引用
收藏
页码:41 / 52
页数:12
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