2012
DOI: 10.26848/rbgf.v5i4.232872
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Trends in precipitation extremes over the Northern part of Brazil from ERA40 dataset (Tendências nos Extremos de Precipitação sobre a Parte Norte do Brasil através dos Dados do ERA40)

Abstract: A B S T R A C TTrends in extreme climate indices were obtained with ERA40 gridded precipitation data over northern Brazil region that includes most of the Amazon Basin and interior of Northeast Brazil. The indices representing one-day highest precipitation in a month, number of rainy days, monthly maximum 5-day consecutive precipitation and number of heavy precipitation days showed increasing trends over most of the grid points of the study region. Although negative trends in wet days were obtained at some gri… Show more

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Cited by 8 publications
(3 citation statements)
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“…In this study, we have calculated all these 11 indices (Table ). Furthermore, for better understanding, the indices were further classified as frequency indices and intensity indices which are adapted from Klein et al (), and dos Santos et al ().…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…In this study, we have calculated all these 11 indices (Table ). Furthermore, for better understanding, the indices were further classified as frequency indices and intensity indices which are adapted from Klein et al (), and dos Santos et al ().…”
Section: Methodsmentioning
confidence: 99%
“…List of Indices as Recommended by ETCCDI and Adapted FromKlein et al (2009) and dosSantos et al (2012) Note. CDD = consecutive dry days; CWD = consecutive wet days; WMO = World Meteorological Organization; SDII = simple daily intensity index.…”
mentioning
confidence: 99%
“…Several studies have indicated the existence of climate change based on trends in climate extreme indices in South America [16][17][18][19][20][21]; however, few of them have considered the regional variability in the Brazilian Midwest. In addition, these studies used monthly and annual averages across the region and disregarded daily data [7] as well as large-scale phenomena such as SST anomalies.…”
Section: Introductionmentioning
confidence: 99%