Premium
Variability and trends in indices of quality‐controlled daily temperature extremes in Uruguay
Author(s) -
Rusticucci Matilde,
Renom Madeleine
Publication year - 2007
Publication title -
international journal of climatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.58
H-Index - 166
eISSN - 1097-0088
pISSN - 0899-8418
DOI - 10.1002/joc.1607
Subject(s) - climatology , environmental science , trend analysis , homogeneity (statistics) , sea surface temperature , geography , statistics , mathematics , geology
Abstract A database of daily extreme temperature was created for as many stations as possible for Uruguay, as far back as possible. This is the first attempt to gather all the different data sources together, perform a quality control and homogeneity assessment. We work with seven stations; it should be taken into account that Uruguay is a small country (around 177 000 km 2 ) and this represents most of the available data. There are three old series with starting dates in 1930, and four that start around 1950. From this database, a set of four extreme temperature indices was constructed for the oldest five stations, warm days (TX90), cold days (TX10), warm nights (TN90) and cold nights (TN10). The index TN10 shows the largest significant negative trend for the period 1960–2002, while TN90 shows a positive but not significant trend for this period indicating a strong warming of nighttime temperature. A spectral analysis was performed using the multi taper methods (MTM) to the de‐trended annual, summer Dec–Feb (DJF) and winter Jun–Aug (JJA) indices time‐series. This analysis shows that on inter‐annual timescales, the most significant range of frequencies is from 2 to 2.5 years and from 3 to 6 years. Low frequencies of variability were detected when the MTM was applied to de‐trended smoothed annual time‐series, around the range of frequencies of 15–25 years for almost all the indices analysed. Links with global sea surface temperature (SST) were studied for two stations (Paysandu and Rocha), and it was found that the indices showed largest correlations with SST anomalies in the Pacific Ocean. We detected changes in the response of the TN10 index for Rocha station when the series was split up into two different periods (1942–1976 and 1977–2005). Copyright © 2007 Royal Meteorological Society