Assessment of local dynamics in extreme precipitation frequency using direct sequential cosimulation

被引:0
作者
Costa, Ana Cristina [1 ]
Soares, Amilcar [2 ]
Pereira, Maria Joao [2 ]
Durao, Rita [2 ]
机构
[1] Univ Nova Lisboa, Inst Super Estatist & Gestao Informacao, Campus Campolide, P-1070312 Lisbon, Portugal
[2] Ctr Recursos Naturais & Ambiente, Inst Super Tecn, P-1049001 Lisbon, Portugal
来源
ENVIRONMENTAL SCIENCE AND SUSTAINABILITY | 2009年
关键词
Climate dynamics; geostatistics; space-time patterns; stochastic simulation; uncertainty; local trends; RAINFALL; TRENDS;
D O I
暂无
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This study evaluates space-time dynamics in extreme precipitation frequency by calculating a climate index at stations with records within the 1940-1999 period in the South of Portugal. This index is based on the annual count of days with precipitation above the 30 mm threshold (R30mm). Direct sequential cosimulation (coDSS) with elevation is used in the spatial interpolation and uncertainty assessment of the extreme precipitation index. The methodology incorporates space-time models that follow the premises that elevation and precipitation extremes may interact differently not only in space, but also through time. The results indicate that the relationship between elevation and the R30mm index has decreased through time over the study region. Moreover, the spatial patterns of precipitation extremes have become more homogenous during the last decades of the twentieth century. The more frequent rainfall events occur in the mountainous areas of the South (Algarve region). Accordingly, many areas of Algarve are at risk of water erosion and floods caused by extreme precipitation events. Regions where the distribution of precipitation extremes shows greater spatial variability, thus more uncertainty, correspond to regions less densely sampled. However, the uncertainty in mountainous regions is noticeably small given that elevation was used as secondary exhaustive information.
引用
收藏
页码:31 / +
页数:2
相关论文
共 17 条
[1]  
[Anonymous], 989 WMO
[2]   Using stochastic space-time models to map extreme precipitation in southern Portugal [J].
Costa, A. C. ;
Durao, R. ;
Pereira, M. J. ;
Soares, A. .
NATURAL HAZARDS AND EARTH SYSTEM SCIENCES, 2008, 8 (04) :763-773
[3]  
COSTA AC, 2009, 12 AGILE C GEOGR INF
[4]   Homogenization of Climate Data: Review and New Perspectives Using Geostatistics [J].
Costa, Ana Cristina ;
Soares, Amilcar .
MATHEMATICAL GEOSCIENCES, 2009, 41 (03) :291-305
[5]   Trends in extreme precipitation indices derived from a daily rainfall database for the South of Portugal [J].
Costa, Ana Cristina ;
Soares, Amilcar .
INTERNATIONAL JOURNAL OF CLIMATOLOGY, 2009, 29 (13) :1956-1975
[6]   Indices of precipitation extremes in Southern Portugal - a geostatistical approach [J].
Durao, R. ;
Pereira, M. J. ;
Costa, A. C. ;
Corte-Real, J. M. ;
Soares, A. .
NATURAL HAZARDS AND EARTH SYSTEM SCIENCES, 2009, 9 (01) :241-250
[7]   Classification of daily abundant rainfall patterns and associated large-scale atmospheric circulation types in Southern Portugal [J].
Fragoso, M. ;
Gomes, P. Tildes .
INTERNATIONAL JOURNAL OF CLIMATOLOGY, 2008, 28 (04) :537-544
[8]   Observed coherent changes in climatic extremes during the second half of the twentieth century [J].
Frich, P ;
Alexander, LV ;
Della-Marta, P ;
Gleason, B ;
Haylock, M ;
Tank, AMGK ;
Peterson, T .
CLIMATE RESEARCH, 2002, 19 (03) :193-212
[9]   Geostatistical approaches for incorporating elevation into the spatial interpolation of rainfall [J].
Goovaerts, P .
JOURNAL OF HYDROLOGY, 2000, 228 (1-2) :113-129
[10]  
Goovaerts P., 1997, APPL GEOSTATISTICS S