Variability and trends in indices of quality-controlled daily temperature extremes in Uruguay

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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 take...

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Autores principales: Rusticucci, M., Renom, M.
Formato: JOUR
Materias:
Extreme temperature indices
Temporal variability
Trends
Uruguay
Customer satisfaction
Problem solving
Quality assurance
Quality function deployment
Total quality management
Data sourcing
Temperature extremes
Quality control
air temperature
data quality
database
extreme event
quality control
temporal variation
trend analysis
South America
Acceso en línea:http://hdl.handle.net/20.500.12110/paper_08998418_v28_n8_p1083_Rusticucci
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires
id todo:paper_08998418_v28_n8_p1083_Rusticucci
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spelling todo:paper_08998418_v28_n8_p1083_Rusticucci2023-10-03T15:44:16Z Variability and trends in indices of quality-controlled daily temperature extremes in Uruguay Rusticucci, M. Renom, M. Extreme temperature indices Temporal variability Trends Uruguay Customer satisfaction Problem solving Quality assurance Quality function deployment Total quality management Data sourcing Temperature extremes Uruguay Quality control air temperature data quality database extreme event quality control temporal variation trend analysis South America Uruguay 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 km2) 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. Fil:Rusticucci, M. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Renom, M. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. JOUR info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_08998418_v28_n8_p1083_Rusticucci
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-134
collection Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic Extreme temperature indices
Temporal variability
Trends
Uruguay
Customer satisfaction
Problem solving
Quality assurance
Quality function deployment
Total quality management
Data sourcing
Temperature extremes
Uruguay
Quality control
air temperature
data quality
database
extreme event
quality control
temporal variation
trend analysis
South America
Uruguay
spellingShingle Extreme temperature indices
Temporal variability
Trends
Uruguay
Customer satisfaction
Problem solving
Quality assurance
Quality function deployment
Total quality management
Data sourcing
Temperature extremes
Uruguay
Quality control
air temperature
data quality
database
extreme event
quality control
temporal variation
trend analysis
South America
Uruguay
Rusticucci, M.
Renom, M.
Variability and trends in indices of quality-controlled daily temperature extremes in Uruguay
topic_facet Extreme temperature indices
Temporal variability
Trends
Uruguay
Customer satisfaction
Problem solving
Quality assurance
Quality function deployment
Total quality management
Data sourcing
Temperature extremes
Uruguay
Quality control
air temperature
data quality
database
extreme event
quality control
temporal variation
trend analysis
South America
Uruguay
description 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 km2) 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.
format JOUR
author Rusticucci, M.
Renom, M.
author_facet Rusticucci, M.
Renom, M.
author_sort Rusticucci, M.
title Variability and trends in indices of quality-controlled daily temperature extremes in Uruguay
title_short Variability and trends in indices of quality-controlled daily temperature extremes in Uruguay
title_full Variability and trends in indices of quality-controlled daily temperature extremes in Uruguay
title_fullStr Variability and trends in indices of quality-controlled daily temperature extremes in Uruguay
title_full_unstemmed Variability and trends in indices of quality-controlled daily temperature extremes in Uruguay
title_sort variability and trends in indices of quality-controlled daily temperature extremes in uruguay
url http://hdl.handle.net/20.500.12110/paper_08998418_v28_n8_p1083_Rusticucci
work_keys_str_mv AT rusticuccim variabilityandtrendsinindicesofqualitycontrolleddailytemperatureextremesinuruguay
AT renomm variabilityandtrendsinindicesofqualitycontrolleddailytemperatureextremesinuruguay
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