Rainfall in Brazilian Northeast via in situ data and CHELSA product: mapping, trends, and socio-environmental implications
Rainfall is a climatic variable that dictates the daily rhythm of urban areas in Northeastern Brazil (NEB) and, therefore, understanding its dynamics is fundamental. The objectives of the study were (i) to validate the CHELSA product with data in situ, (ii) assess the spatial-temporality of the rain...
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| creator | de Oliveira-Júnior, José Francisco Correia Filho, Washington Luiz Félix de Barros Santiago, Dimas de Gois, Givanildo da Silva Costa, Micejane da Silva Junior, Carlos Antonio Teodoro, Paulo Eduardo Freire, Felipe Machado |
| description | Rainfall is a climatic variable that dictates the daily rhythm of urban areas in Northeastern Brazil (NEB) and, therefore, understanding its dynamics is fundamental. The objectives of the study were (i) to validate the CHELSA product with data in situ, (ii) assess the spatial-temporality of the rains, and (iii) assess the trends and socio-environmental implications in the Metropolitan Region of Maceió (MRM). The monthly rainfall data observed between 1960 and 2016 were flawed and were filled with the imputation of data. These series were subjected to descriptive and exploratory statistics, statistical indicators, and the Mann–Kendall (MK) and Pettitt tests. CHELSA product was validated for MRM, and all stations obtained satisfactory determination coefficients (
R
2
) and Pearson correlation (
r
). The standard error of the estimate (SEE), root mean square error (RMSE), and mean absolute error (MAE) were satisfactory. The highest annual rainfall accumulated occurred near the Mundaú and Manguaba lagoons. The Pettitt test identified that abrupt changes occur in El Niño and La Niña years (strong and weak). The monthly rain boxplots showed high variability in the rainy season (April–July). Outliers have been associated with extreme rainfall at MRM. The drought period was 5 months in all MRM seasons, except in Satuba and Pilar. The Mann–Kendall test and the Sen method showed a tendency for a significant increase in rainfall in Satuba and not significant in the Pilar, while in the others, there was a tendency for a decrease in rainfall. The MRM rainfall depends on physiographic factors, multiscale meteorological systems, and the coastal environment. These results will assist in planning conservationist practices, especially in areas of socio-environmental vulnerability. |
| doi_str_mv | 10.1007/s10661-021-09043-9 |
| format | Article |
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R
2
) and Pearson correlation (
r
). The standard error of the estimate (SEE), root mean square error (RMSE), and mean absolute error (MAE) were satisfactory. The highest annual rainfall accumulated occurred near the Mundaú and Manguaba lagoons. The Pettitt test identified that abrupt changes occur in El Niño and La Niña years (strong and weak). The monthly rain boxplots showed high variability in the rainy season (April–July). Outliers have been associated with extreme rainfall at MRM. The drought period was 5 months in all MRM seasons, except in Satuba and Pilar. The Mann–Kendall test and the Sen method showed a tendency for a significant increase in rainfall in Satuba and not significant in the Pilar, while in the others, there was a tendency for a decrease in rainfall. The MRM rainfall depends on physiographic factors, multiscale meteorological systems, and the coastal environment. These results will assist in planning conservationist practices, especially in areas of socio-environmental vulnerability.</description><identifier>ISSN: 0167-6369</identifier><identifier>EISSN: 1573-2959</identifier><identifier>DOI: 10.1007/s10661-021-09043-9</identifier><identifier>PMID: 33847840</identifier><language>eng</language><publisher>Cham: Springer International Publishing</publisher><subject>Annual rainfall ; Atmospheric Protection/Air Quality Control/Air Pollution ; Brazil ; Climate change ; Coastal environments ; Coastal zones ; Coefficients ; Data ; Drought ; Earth and Environmental Science ; Ecology ; Ecotoxicology ; El Nino ; El Nino phenomena ; El Nino-Southern Oscillation ; Environment ; Environmental impact ; Environmental Management ; Environmental Monitoring ; Environmental science ; Extreme weather ; Hydrologic data ; La Nina ; Lagoons ; Metropolitan areas ; Monitoring/Environmental Analysis ; Monthly rainfall ; Monthly rainfall data ; Outliers (statistics) ; Rain ; Rainfall ; Rainfall data ; Rainy season ; Root-mean-square errors ; Seasons ; Standard error ; Statistical methods ; Statistical tests ; Trends ; Urban areas ; Vulnerability ; Wet season</subject><ispartof>Environmental monitoring and assessment, 2021-05, Vol.193 (5), p.263, Article 263</ispartof><rights>The Author(s), under exclusive licence to Springer Nature Switzerland AG 2021</rights><rights>The Author(s), under exclusive licence to Springer Nature Switzerland AG 2021.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c375t-8d9c3d232cdd19046898789436fcb8f6576435d624b3af1863df96a7cdec741e3</citedby><cites>FETCH-LOGICAL-c375t-8d9c3d232cdd19046898789436fcb8f6576435d624b3af1863df96a7cdec741e3</cites><orcidid>0000-0002-7102-2077</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10661-021-09043-9$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10661-021-09043-9$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33847840$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>de Oliveira-Júnior, José Francisco</creatorcontrib><creatorcontrib>Correia Filho, Washington Luiz Félix</creatorcontrib><creatorcontrib>de Barros Santiago, Dimas</creatorcontrib><creatorcontrib>de Gois, Givanildo</creatorcontrib><creatorcontrib>da Silva Costa, Micejane</creatorcontrib><creatorcontrib>da Silva Junior, Carlos Antonio</creatorcontrib><creatorcontrib>Teodoro, Paulo Eduardo</creatorcontrib><creatorcontrib>Freire, Felipe Machado</creatorcontrib><title>Rainfall in Brazilian Northeast via in situ data and CHELSA product: mapping, trends, and socio-environmental implications</title><title>Environmental monitoring and assessment</title><addtitle>Environ Monit Assess</addtitle><addtitle>Environ Monit Assess</addtitle><description>Rainfall is a climatic variable that dictates the daily rhythm of urban areas in Northeastern Brazil (NEB) and, therefore, understanding its dynamics is fundamental. The objectives of the study were (i) to validate the CHELSA product with data in situ, (ii) assess the spatial-temporality of the rains, and (iii) assess the trends and socio-environmental implications in the Metropolitan Region of Maceió (MRM). The monthly rainfall data observed between 1960 and 2016 were flawed and were filled with the imputation of data. These series were subjected to descriptive and exploratory statistics, statistical indicators, and the Mann–Kendall (MK) and Pettitt tests. CHELSA product was validated for MRM, and all stations obtained satisfactory determination coefficients (
R
2
) and Pearson correlation (
r
). The standard error of the estimate (SEE), root mean square error (RMSE), and mean absolute error (MAE) were satisfactory. The highest annual rainfall accumulated occurred near the Mundaú and Manguaba lagoons. The Pettitt test identified that abrupt changes occur in El Niño and La Niña years (strong and weak). The monthly rain boxplots showed high variability in the rainy season (April–July). Outliers have been associated with extreme rainfall at MRM. The drought period was 5 months in all MRM seasons, except in Satuba and Pilar. The Mann–Kendall test and the Sen method showed a tendency for a significant increase in rainfall in Satuba and not significant in the Pilar, while in the others, there was a tendency for a decrease in rainfall. The MRM rainfall depends on physiographic factors, multiscale meteorological systems, and the coastal environment. These results will assist in planning conservationist practices, especially in areas of socio-environmental vulnerability.</description><subject>Annual rainfall</subject><subject>Atmospheric Protection/Air Quality Control/Air Pollution</subject><subject>Brazil</subject><subject>Climate change</subject><subject>Coastal environments</subject><subject>Coastal zones</subject><subject>Coefficients</subject><subject>Data</subject><subject>Drought</subject><subject>Earth and Environmental Science</subject><subject>Ecology</subject><subject>Ecotoxicology</subject><subject>El Nino</subject><subject>El Nino phenomena</subject><subject>El Nino-Southern Oscillation</subject><subject>Environment</subject><subject>Environmental impact</subject><subject>Environmental Management</subject><subject>Environmental Monitoring</subject><subject>Environmental science</subject><subject>Extreme weather</subject><subject>Hydrologic data</subject><subject>La Nina</subject><subject>Lagoons</subject><subject>Metropolitan areas</subject><subject>Monitoring/Environmental Analysis</subject><subject>Monthly rainfall</subject><subject>Monthly rainfall data</subject><subject>Outliers (statistics)</subject><subject>Rain</subject><subject>Rainfall</subject><subject>Rainfall data</subject><subject>Rainy season</subject><subject>Root-mean-square errors</subject><subject>Seasons</subject><subject>Standard error</subject><subject>Statistical methods</subject><subject>Statistical tests</subject><subject>Trends</subject><subject>Urban areas</subject><subject>Vulnerability</subject><subject>Wet 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in Brazilian Northeast via in situ data and CHELSA product: mapping, trends, and socio-environmental implications</title><author>de Oliveira-Júnior, José Francisco ; Correia Filho, Washington Luiz Félix ; de Barros Santiago, Dimas ; de Gois, Givanildo ; da Silva Costa, Micejane ; da Silva Junior, Carlos Antonio ; Teodoro, Paulo Eduardo ; Freire, Felipe Machado</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c375t-8d9c3d232cdd19046898789436fcb8f6576435d624b3af1863df96a7cdec741e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Annual rainfall</topic><topic>Atmospheric Protection/Air Quality Control/Air Pollution</topic><topic>Brazil</topic><topic>Climate change</topic><topic>Coastal environments</topic><topic>Coastal zones</topic><topic>Coefficients</topic><topic>Data</topic><topic>Drought</topic><topic>Earth and Environmental 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Antonio</au><au>Teodoro, Paulo Eduardo</au><au>Freire, Felipe Machado</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Rainfall in Brazilian Northeast via in situ data and CHELSA product: mapping, trends, and socio-environmental implications</atitle><jtitle>Environmental monitoring and assessment</jtitle><stitle>Environ Monit Assess</stitle><addtitle>Environ Monit Assess</addtitle><date>2021-05-01</date><risdate>2021</risdate><volume>193</volume><issue>5</issue><spage>263</spage><pages>263-</pages><artnum>263</artnum><issn>0167-6369</issn><eissn>1573-2959</eissn><abstract>Rainfall is a climatic variable that dictates the daily rhythm of urban areas in Northeastern Brazil (NEB) and, therefore, understanding its dynamics is fundamental. The objectives of the study were (i) to validate the CHELSA product with data in situ, (ii) assess the spatial-temporality of the rains, and (iii) assess the trends and socio-environmental implications in the Metropolitan Region of Maceió (MRM). The monthly rainfall data observed between 1960 and 2016 were flawed and were filled with the imputation of data. These series were subjected to descriptive and exploratory statistics, statistical indicators, and the Mann–Kendall (MK) and Pettitt tests. CHELSA product was validated for MRM, and all stations obtained satisfactory determination coefficients (
R
2
) and Pearson correlation (
r
). The standard error of the estimate (SEE), root mean square error (RMSE), and mean absolute error (MAE) were satisfactory. The highest annual rainfall accumulated occurred near the Mundaú and Manguaba lagoons. The Pettitt test identified that abrupt changes occur in El Niño and La Niña years (strong and weak). The monthly rain boxplots showed high variability in the rainy season (April–July). Outliers have been associated with extreme rainfall at MRM. The drought period was 5 months in all MRM seasons, except in Satuba and Pilar. The Mann–Kendall test and the Sen method showed a tendency for a significant increase in rainfall in Satuba and not significant in the Pilar, while in the others, there was a tendency for a decrease in rainfall. The MRM rainfall depends on physiographic factors, multiscale meteorological systems, and the coastal environment. These results will assist in planning conservationist practices, especially in areas of socio-environmental vulnerability.</abstract><cop>Cham</cop><pub>Springer International Publishing</pub><pmid>33847840</pmid><doi>10.1007/s10661-021-09043-9</doi><orcidid>https://orcid.org/0000-0002-7102-2077</orcidid></addata></record> |
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| ispartof | Environmental monitoring and assessment, 2021-05, Vol.193 (5), p.263, Article 263 |
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| language | eng |
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| source | MEDLINE; Springer Nature - Complete Springer Journals |
| subjects | Annual rainfall Atmospheric Protection/Air Quality Control/Air Pollution Brazil Climate change Coastal environments Coastal zones Coefficients Data Drought Earth and Environmental Science Ecology Ecotoxicology El Nino El Nino phenomena El Nino-Southern Oscillation Environment Environmental impact Environmental Management Environmental Monitoring Environmental science Extreme weather Hydrologic data La Nina Lagoons Metropolitan areas Monitoring/Environmental Analysis Monthly rainfall Monthly rainfall data Outliers (statistics) Rain Rainfall Rainfall data Rainy season Root-mean-square errors Seasons Standard error Statistical methods Statistical tests Trends Urban areas Vulnerability Wet season |
| title | Rainfall in Brazilian Northeast via in situ data and CHELSA product: mapping, trends, and socio-environmental implications |
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