No abstract

ABSTRACT:The rainfall regime of the South of Portugal is Mediterranean with Atlantic influence. Long-term series of reliable precipitation records are essential for land and water resources management, climate-change monitoring, modelling of erosion and run-off, among other applications for ecosystem and hydrological impact modelling. This study provides a qualitative classification of 106 daily rainfall series from stations located in the South of Portugal and evaluates temporal patterns in extreme precipitation by calculating a number of indicators at stations with homogeneous data within the 1955/1999 period. The methodology includes both absolute and relative approaches and a new homogeneity testing procedure, besides the application of other statistical tests. The proposed technique is an extension of the Ellipse test that takes into account the contemporaneous relationship between several candidate series from the same climatic area (SUR+Ellipse test). The results indicate that this technique is a valuable tool for the detection of non-climatic irregularities in climate time series if the station network is dense enough. The existence of trends and other temporal patterns in extreme precipitation indices was investigated and uncertainty about rainfall patterns evolution was assessed. Three indices describing wet events and another three indicators characterizing dry conditions were analysed through regression models and smoothing techniques. The simple aridity intensity index (AII) reflects increases in the magnitude of dryness. Especially pronounced trends are found over most of southern Portugal in the 1955/1999 period, highlighting the fact that large areas are threatened by drought and desertification. The trend signals of the wetness indices are not significant at the majority of stations, but there is evidence of increasing short-term precipitation intensity over the region during the last three decades of the twentieth century. Finally, the results also indicate that extreme precipitation variability and climate uncertainty are greater in recent times.

No abstract

No abstract

No abstract