THE INFLUENCE OF THE REMOTELY SENSED RAINFALL PRODUCTS’ SPATIAL RESOLUTION TO UNMASK EXTREME EVENTS IN NORTHEAST BRAZIL

This work presents the influence of the spatial resolution on precipitation samples to understand extreme events in the Agreste region of Pernambuco, northeast of Brazil. Among the materials used, the following sources of precipitation data (1998 to 2019) can be cited: The Tropical Rainfall Measurin...

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Autores: Nova, Raquel Arcoverde Vila, Gonçalves, Rodrigo Mikosz, Ferreira, Lígia Albuquerque de Alcântara, Lima, Fábio Vinícius Marley Santos
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2022
País:Brasil
Institución:Universidade Federal do Paraná (UFPR)
Repositorio:Boletim de Ciências Geodésicas
Idioma:inglés
OAI Identifier:oai:ojs.pkp.sfu.ca:article/84201
Acceso en línea:https://revistas.ufpr.br/bcg/article/view/84201
Access Level:acceso abierto
Palabra clave:Precipitation
Climate extremes
TRMM
CRU
SPI.
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spelling THE INFLUENCE OF THE REMOTELY SENSED RAINFALL PRODUCTS’ SPATIAL RESOLUTION TO UNMASK EXTREME EVENTS IN NORTHEAST BRAZILPrecipitationClimate extremesTRMMCRUSPI.This work presents the influence of the spatial resolution on precipitation samples to understand extreme events in the Agreste region of Pernambuco, northeast of Brazil. Among the materials used, the following sources of precipitation data (1998 to 2019) can be cited: The Tropical Rainfall Measuring Mission (TRMM), the Climatic Research Unit (CRU), and weather stations. In the process of validating the precipitation time series with the weather stations, the TRMM data showed a strong Pearson correlation (0.86 - 0.90) and the CRU data a moderate one (0.71 - 0.76). The relative bias (RB) and the standard deviation of observation ratio (RSR) were also calculated to identify the data’s trend, which showed an overestimation for both sources. The extreme events were identified through the calculation of the Standardized Precipitation Index (SPI), where the TRMM with strong correlation (0.80 - 0.91) obtained a better performance than the CRU data. The TRMM data were selected to understand the extreme drought events in the study area, where the cities with altitudes above 500m obtained maximum values of probability of occurrence with 19%. Conversely, for extreme humidity events, the maximum was 14% for those with altitudes below 200m.Boletim de Ciências GeodésicasBulletin of Geodetic Sciences2022-01-03info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://revistas.ufpr.br/bcg/article/view/84201Boletim de Ciências Geodésicas; v. 27 n. 3 (2021)Bulletin of Geodetic Sciences; Vol. 27 No. 3 (2021)1982-21701413-4853reponame:Boletim de Ciências Geodésicasinstname:Universidade Federal do Paraná (UFPR)instacron:UFPRenghttps://revistas.ufpr.br/bcg/article/view/84201/45593Copyright (c) 2022 Raquel Arcoverde Vila Nova, Rodrigo Mikosz Gonçalves, Lígia Albuquerque de Alcântara Ferreira, Fábio Vinícius Marley Santos Limainfo:eu-repo/semantics/openAccessNova, Raquel Arcoverde VilaGonçalves, Rodrigo MikoszFerreira, Lígia Albuquerque de AlcântaraLima, Fábio Vinícius Marley Santos2022-01-03T16:07:23Zoai:ojs.pkp.sfu.ca:article/84201Revistahttps://revistas.ufpr.br/bcgPUBhttps://revistas.ufpr.br/bcg/oaiqdalmolin@ufpr.br|| danielsantos@ufpr.br||qdalmolin@ufpr.br|| danielsantos@ufpr.br|| bcg_editor@ufpr.br1982-21701413-4853opendoar:2022-01-03T16:07:23Boletim de Ciências Geodésicas - Universidade Federal do Paraná (UFPR)false
dc.title.none.fl_str_mv THE INFLUENCE OF THE REMOTELY SENSED RAINFALL PRODUCTS’ SPATIAL RESOLUTION TO UNMASK EXTREME EVENTS IN NORTHEAST BRAZIL
title THE INFLUENCE OF THE REMOTELY SENSED RAINFALL PRODUCTS’ SPATIAL RESOLUTION TO UNMASK EXTREME EVENTS IN NORTHEAST BRAZIL
spellingShingle THE INFLUENCE OF THE REMOTELY SENSED RAINFALL PRODUCTS’ SPATIAL RESOLUTION TO UNMASK EXTREME EVENTS IN NORTHEAST BRAZIL
Nova, Raquel Arcoverde Vila
Precipitation
Climate extremes
TRMM
CRU
SPI.
title_short THE INFLUENCE OF THE REMOTELY SENSED RAINFALL PRODUCTS’ SPATIAL RESOLUTION TO UNMASK EXTREME EVENTS IN NORTHEAST BRAZIL
title_full THE INFLUENCE OF THE REMOTELY SENSED RAINFALL PRODUCTS’ SPATIAL RESOLUTION TO UNMASK EXTREME EVENTS IN NORTHEAST BRAZIL
title_fullStr THE INFLUENCE OF THE REMOTELY SENSED RAINFALL PRODUCTS’ SPATIAL RESOLUTION TO UNMASK EXTREME EVENTS IN NORTHEAST BRAZIL
title_full_unstemmed THE INFLUENCE OF THE REMOTELY SENSED RAINFALL PRODUCTS’ SPATIAL RESOLUTION TO UNMASK EXTREME EVENTS IN NORTHEAST BRAZIL
title_sort THE INFLUENCE OF THE REMOTELY SENSED RAINFALL PRODUCTS’ SPATIAL RESOLUTION TO UNMASK EXTREME EVENTS IN NORTHEAST BRAZIL
dc.creator.none.fl_str_mv Nova, Raquel Arcoverde Vila
Gonçalves, Rodrigo Mikosz
Ferreira, Lígia Albuquerque de Alcântara
Lima, Fábio Vinícius Marley Santos
author Nova, Raquel Arcoverde Vila
author_facet Nova, Raquel Arcoverde Vila
Gonçalves, Rodrigo Mikosz
Ferreira, Lígia Albuquerque de Alcântara
Lima, Fábio Vinícius Marley Santos
author_role author
author2 Gonçalves, Rodrigo Mikosz
Ferreira, Lígia Albuquerque de Alcântara
Lima, Fábio Vinícius Marley Santos
author2_role author
author
author
dc.subject.por.fl_str_mv Precipitation
Climate extremes
TRMM
CRU
SPI.
topic Precipitation
Climate extremes
TRMM
CRU
SPI.
description This work presents the influence of the spatial resolution on precipitation samples to understand extreme events in the Agreste region of Pernambuco, northeast of Brazil. Among the materials used, the following sources of precipitation data (1998 to 2019) can be cited: The Tropical Rainfall Measuring Mission (TRMM), the Climatic Research Unit (CRU), and weather stations. In the process of validating the precipitation time series with the weather stations, the TRMM data showed a strong Pearson correlation (0.86 - 0.90) and the CRU data a moderate one (0.71 - 0.76). The relative bias (RB) and the standard deviation of observation ratio (RSR) were also calculated to identify the data’s trend, which showed an overestimation for both sources. The extreme events were identified through the calculation of the Standardized Precipitation Index (SPI), where the TRMM with strong correlation (0.80 - 0.91) obtained a better performance than the CRU data. The TRMM data were selected to understand the extreme drought events in the study area, where the cities with altitudes above 500m obtained maximum values of probability of occurrence with 19%. Conversely, for extreme humidity events, the maximum was 14% for those with altitudes below 200m.
publishDate 2022
dc.date.none.fl_str_mv 2022-01-03
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://revistas.ufpr.br/bcg/article/view/84201
url https://revistas.ufpr.br/bcg/article/view/84201
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://revistas.ufpr.br/bcg/article/view/84201/45593
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Boletim de Ciências Geodésicas
Bulletin of Geodetic Sciences
publisher.none.fl_str_mv Boletim de Ciências Geodésicas
Bulletin of Geodetic Sciences
dc.source.none.fl_str_mv Boletim de Ciências Geodésicas; v. 27 n. 3 (2021)
Bulletin of Geodetic Sciences; Vol. 27 No. 3 (2021)
1982-2170
1413-4853
reponame:Boletim de Ciências Geodésicas
instname:Universidade Federal do Paraná (UFPR)
instacron:UFPR
instname_str Universidade Federal do Paraná (UFPR)
instacron_str UFPR
institution UFPR
reponame_str Boletim de Ciências Geodésicas
collection Boletim de Ciências Geodésicas
repository.name.fl_str_mv Boletim de Ciências Geodésicas - Universidade Federal do Paraná (UFPR)
repository.mail.fl_str_mv qdalmolin@ufpr.br|| danielsantos@ufpr.br||qdalmolin@ufpr.br|| danielsantos@ufpr.br|| bcg_editor@ufpr.br
_version_ 1853676226011463680
score 15,223283

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