Loading…
Exploring climate extremes in Brazil’s Legal Amazon
In this study, we evaluated extreme climate indicators for precipitation and temperature in the Brazilian Legal Amazon (BLA) from 1961 to 2021. Data from 38 National Institute of Meteorology (INMET) weather stations with a record failure rate less than 12% were used, and RClimDex software and the Ma...
Saved in:
| Published in: | Stochastic environmental research and risk assessment 2024-04, Vol.38 (4), p.1403-1422 |
|---|---|
| Main Authors: | , , , , , , , |
| Format: | Article |
| Language: | English |
| Subjects: | |
| Citations: | Items that this one cites |
| Online Access: | Get full text |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| cited_by | |
|---|---|
| cites | cdi_FETCH-LOGICAL-c270t-a8d7264b0200acf05d95ad2a1064e016f82f5a91a41ec5082531eab615a2d4e3 |
| container_end_page | 1422 |
| container_issue | 4 |
| container_start_page | 1403 |
| container_title | Stochastic environmental research and risk assessment |
| container_volume | 38 |
| creator | de Bodas Terassi, Paulo Miguel Galvani, Emerson Gobo, João Paulo Assis da Silva Oscar-Júnior, Antonio Carlos Luiz-Silva, Wanderson Sobral, Bruno Serafini de Gois, Givanildo Biffi, Vitor Hugo Rosa |
| description | In this study, we evaluated extreme climate indicators for precipitation and temperature in the Brazilian Legal Amazon (BLA) from 1961 to 2021. Data from 38 National Institute of Meteorology (INMET) weather stations with a record failure rate less than 12% were used, and RClimDex software and the Mann–Kendall test, Pettitt test, standard normal homogeneity test (SNHT), and Buishand test were employed to analyse the data. The results showed increased extreme rainfall events, including the annual total rainfall divided by wet days (SDII). More frequent discontinuities were observed in the 1980s (SNHT) and 1990s (Pettitt and Buishand tests). The extreme temperature climate indicators also significantly increased, particularly in the 1990s. These increases are likely linked to changes in local climate conditions due to agricultural expansion, intensified industrial activities, and regional urbanization. This study underscores the need for proactive measures to curb illegal deforestation and reduce CO
2
emissions and further research to better understand and mitigate the adverse impacts of these changes on the BLA environment and local communities.
Graphical abstract |
| doi_str_mv | 10.1007/s00477-023-02634-7 |
| format | article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2983468369</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2983468369</sourcerecordid><originalsourceid>FETCH-LOGICAL-c270t-a8d7264b0200acf05d95ad2a1064e016f82f5a91a41ec5082531eab615a2d4e3</originalsourceid><addsrcrecordid>eNp9kM1Kw1AQhS-iYK2-gKuA6-jc_2RZS_2BgJvuL9NkUlLSJN6bQu3K1_D1fBJTI7pzMcwszjnD-Ri75nDLAexdAFDWxiDkMEaq2J6wCVfSxFLo9PT3VnDOLkLYAHBrtZowvdh3deurZh3ldbXFniLa9562FKKqie49Hqr68_0jRBmtsY5mWzy0zSU7K7EOdPWzp2z5sFjOn-Ls5fF5PsviXFjoY0wKK4xagQDAvARdpBoLgRyMIuCmTESpMeWoOOUaEqElJ1wZrlEUiuSU3YyxnW9fdxR6t2l3vhk-OpEmUplEmnRQiVGV-zYET6Xr_NDEvzkO7kjHjXTcQMd903F2MMnRFLpjefJ_0f-4vgB312cE</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2983468369</pqid></control><display><type>article</type><title>Exploring climate extremes in Brazil’s Legal Amazon</title><source>Springer Link</source><creator>de Bodas Terassi, Paulo Miguel ; Galvani, Emerson ; Gobo, João Paulo Assis ; da Silva Oscar-Júnior, Antonio Carlos ; Luiz-Silva, Wanderson ; Sobral, Bruno Serafini ; de Gois, Givanildo ; Biffi, Vitor Hugo Rosa</creator><creatorcontrib>de Bodas Terassi, Paulo Miguel ; Galvani, Emerson ; Gobo, João Paulo Assis ; da Silva Oscar-Júnior, Antonio Carlos ; Luiz-Silva, Wanderson ; Sobral, Bruno Serafini ; de Gois, Givanildo ; Biffi, Vitor Hugo Rosa</creatorcontrib><description>In this study, we evaluated extreme climate indicators for precipitation and temperature in the Brazilian Legal Amazon (BLA) from 1961 to 2021. Data from 38 National Institute of Meteorology (INMET) weather stations with a record failure rate less than 12% were used, and RClimDex software and the Mann–Kendall test, Pettitt test, standard normal homogeneity test (SNHT), and Buishand test were employed to analyse the data. The results showed increased extreme rainfall events, including the annual total rainfall divided by wet days (SDII). More frequent discontinuities were observed in the 1980s (SNHT) and 1990s (Pettitt and Buishand tests). The extreme temperature climate indicators also significantly increased, particularly in the 1990s. These increases are likely linked to changes in local climate conditions due to agricultural expansion, intensified industrial activities, and regional urbanization. This study underscores the need for proactive measures to curb illegal deforestation and reduce CO
2
emissions and further research to better understand and mitigate the adverse impacts of these changes on the BLA environment and local communities.
Graphical abstract</description><identifier>ISSN: 1436-3240</identifier><identifier>EISSN: 1436-3259</identifier><identifier>DOI: 10.1007/s00477-023-02634-7</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Agricultural expansion ; Aquatic Pollution ; Biodiversity ; Carbon dioxide ; Carbon dioxide emissions ; Chemistry and Earth Sciences ; Climate ; Climate change ; Climatic conditions ; Computational Intelligence ; Computer Science ; Deforestation ; Earth and Environmental Science ; Earth Sciences ; Ecosystems ; Environment ; Environmental research ; Extreme values ; Extreme weather ; Forests ; Homogeneity ; Indicators ; Industrial areas ; Local communities ; Math. Appl. in Environmental Science ; Meteorology ; Missing data ; Original Paper ; Physics ; Precipitation ; Probability Theory and Stochastic Processes ; Rain ; Rainfall ; Risk assessment ; Statistics for Engineering ; Time series ; Trends ; Urbanization ; Waste Water Technology ; Water Management ; Water Pollution Control ; Weather stations</subject><ispartof>Stochastic environmental research and risk assessment, 2024-04, Vol.38 (4), p.1403-1422</ispartof><rights>The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c270t-a8d7264b0200acf05d95ad2a1064e016f82f5a91a41ec5082531eab615a2d4e3</cites><orcidid>0000-0002-5773-7842 ; 0000-0003-4461-2570 ; 0000-0002-8438-2055 ; 0000-0002-8184-0348 ; 0000-0002-8082-5963 ; 0000-0001-8589-7301 ; 0000-0002-2583-5245 ; 0000-0001-9751-5884</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>de Bodas Terassi, Paulo Miguel</creatorcontrib><creatorcontrib>Galvani, Emerson</creatorcontrib><creatorcontrib>Gobo, João Paulo Assis</creatorcontrib><creatorcontrib>da Silva Oscar-Júnior, Antonio Carlos</creatorcontrib><creatorcontrib>Luiz-Silva, Wanderson</creatorcontrib><creatorcontrib>Sobral, Bruno Serafini</creatorcontrib><creatorcontrib>de Gois, Givanildo</creatorcontrib><creatorcontrib>Biffi, Vitor Hugo Rosa</creatorcontrib><title>Exploring climate extremes in Brazil’s Legal Amazon</title><title>Stochastic environmental research and risk assessment</title><addtitle>Stoch Environ Res Risk Assess</addtitle><description>In this study, we evaluated extreme climate indicators for precipitation and temperature in the Brazilian Legal Amazon (BLA) from 1961 to 2021. Data from 38 National Institute of Meteorology (INMET) weather stations with a record failure rate less than 12% were used, and RClimDex software and the Mann–Kendall test, Pettitt test, standard normal homogeneity test (SNHT), and Buishand test were employed to analyse the data. The results showed increased extreme rainfall events, including the annual total rainfall divided by wet days (SDII). More frequent discontinuities were observed in the 1980s (SNHT) and 1990s (Pettitt and Buishand tests). The extreme temperature climate indicators also significantly increased, particularly in the 1990s. These increases are likely linked to changes in local climate conditions due to agricultural expansion, intensified industrial activities, and regional urbanization. This study underscores the need for proactive measures to curb illegal deforestation and reduce CO
2
emissions and further research to better understand and mitigate the adverse impacts of these changes on the BLA environment and local communities.
Graphical abstract</description><subject>Agricultural expansion</subject><subject>Aquatic Pollution</subject><subject>Biodiversity</subject><subject>Carbon dioxide</subject><subject>Carbon dioxide emissions</subject><subject>Chemistry and Earth Sciences</subject><subject>Climate</subject><subject>Climate change</subject><subject>Climatic conditions</subject><subject>Computational Intelligence</subject><subject>Computer Science</subject><subject>Deforestation</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Ecosystems</subject><subject>Environment</subject><subject>Environmental research</subject><subject>Extreme values</subject><subject>Extreme weather</subject><subject>Forests</subject><subject>Homogeneity</subject><subject>Indicators</subject><subject>Industrial areas</subject><subject>Local communities</subject><subject>Math. Appl. in Environmental Science</subject><subject>Meteorology</subject><subject>Missing data</subject><subject>Original Paper</subject><subject>Physics</subject><subject>Precipitation</subject><subject>Probability Theory and Stochastic Processes</subject><subject>Rain</subject><subject>Rainfall</subject><subject>Risk assessment</subject><subject>Statistics for Engineering</subject><subject>Time series</subject><subject>Trends</subject><subject>Urbanization</subject><subject>Waste Water Technology</subject><subject>Water Management</subject><subject>Water Pollution Control</subject><subject>Weather stations</subject><issn>1436-3240</issn><issn>1436-3259</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNp9kM1Kw1AQhS-iYK2-gKuA6-jc_2RZS_2BgJvuL9NkUlLSJN6bQu3K1_D1fBJTI7pzMcwszjnD-Ri75nDLAexdAFDWxiDkMEaq2J6wCVfSxFLo9PT3VnDOLkLYAHBrtZowvdh3deurZh3ldbXFniLa9562FKKqie49Hqr68_0jRBmtsY5mWzy0zSU7K7EOdPWzp2z5sFjOn-Ls5fF5PsviXFjoY0wKK4xagQDAvARdpBoLgRyMIuCmTESpMeWoOOUaEqElJ1wZrlEUiuSU3YyxnW9fdxR6t2l3vhk-OpEmUplEmnRQiVGV-zYET6Xr_NDEvzkO7kjHjXTcQMd903F2MMnRFLpjefJ_0f-4vgB312cE</recordid><startdate>20240401</startdate><enddate>20240401</enddate><creator>de Bodas Terassi, Paulo Miguel</creator><creator>Galvani, Emerson</creator><creator>Gobo, João Paulo Assis</creator><creator>da Silva Oscar-Júnior, Antonio Carlos</creator><creator>Luiz-Silva, Wanderson</creator><creator>Sobral, Bruno Serafini</creator><creator>de Gois, Givanildo</creator><creator>Biffi, Vitor Hugo Rosa</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7ST</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>KR7</scope><scope>SOI</scope><orcidid>https://orcid.org/0000-0002-5773-7842</orcidid><orcidid>https://orcid.org/0000-0003-4461-2570</orcidid><orcidid>https://orcid.org/0000-0002-8438-2055</orcidid><orcidid>https://orcid.org/0000-0002-8184-0348</orcidid><orcidid>https://orcid.org/0000-0002-8082-5963</orcidid><orcidid>https://orcid.org/0000-0001-8589-7301</orcidid><orcidid>https://orcid.org/0000-0002-2583-5245</orcidid><orcidid>https://orcid.org/0000-0001-9751-5884</orcidid></search><sort><creationdate>20240401</creationdate><title>Exploring climate extremes in Brazil’s Legal Amazon</title><author>de Bodas Terassi, Paulo Miguel ; Galvani, Emerson ; Gobo, João Paulo Assis ; da Silva Oscar-Júnior, Antonio Carlos ; Luiz-Silva, Wanderson ; Sobral, Bruno Serafini ; de Gois, Givanildo ; Biffi, Vitor Hugo Rosa</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c270t-a8d7264b0200acf05d95ad2a1064e016f82f5a91a41ec5082531eab615a2d4e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Agricultural expansion</topic><topic>Aquatic Pollution</topic><topic>Biodiversity</topic><topic>Carbon dioxide</topic><topic>Carbon dioxide emissions</topic><topic>Chemistry and Earth Sciences</topic><topic>Climate</topic><topic>Climate change</topic><topic>Climatic conditions</topic><topic>Computational Intelligence</topic><topic>Computer Science</topic><topic>Deforestation</topic><topic>Earth and Environmental Science</topic><topic>Earth Sciences</topic><topic>Ecosystems</topic><topic>Environment</topic><topic>Environmental research</topic><topic>Extreme values</topic><topic>Extreme weather</topic><topic>Forests</topic><topic>Homogeneity</topic><topic>Indicators</topic><topic>Industrial areas</topic><topic>Local communities</topic><topic>Math. Appl. in Environmental Science</topic><topic>Meteorology</topic><topic>Missing data</topic><topic>Original Paper</topic><topic>Physics</topic><topic>Precipitation</topic><topic>Probability Theory and Stochastic Processes</topic><topic>Rain</topic><topic>Rainfall</topic><topic>Risk assessment</topic><topic>Statistics for Engineering</topic><topic>Time series</topic><topic>Trends</topic><topic>Urbanization</topic><topic>Waste Water Technology</topic><topic>Water Management</topic><topic>Water Pollution Control</topic><topic>Weather stations</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>de Bodas Terassi, Paulo Miguel</creatorcontrib><creatorcontrib>Galvani, Emerson</creatorcontrib><creatorcontrib>Gobo, João Paulo Assis</creatorcontrib><creatorcontrib>da Silva Oscar-Júnior, Antonio Carlos</creatorcontrib><creatorcontrib>Luiz-Silva, Wanderson</creatorcontrib><creatorcontrib>Sobral, Bruno Serafini</creatorcontrib><creatorcontrib>de Gois, Givanildo</creatorcontrib><creatorcontrib>Biffi, Vitor Hugo Rosa</creatorcontrib><collection>CrossRef</collection><collection>Environment Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>Civil Engineering Abstracts</collection><collection>Environment Abstracts</collection><jtitle>Stochastic environmental research and risk assessment</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>de Bodas Terassi, Paulo Miguel</au><au>Galvani, Emerson</au><au>Gobo, João Paulo Assis</au><au>da Silva Oscar-Júnior, Antonio Carlos</au><au>Luiz-Silva, Wanderson</au><au>Sobral, Bruno Serafini</au><au>de Gois, Givanildo</au><au>Biffi, Vitor Hugo Rosa</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Exploring climate extremes in Brazil’s Legal Amazon</atitle><jtitle>Stochastic environmental research and risk assessment</jtitle><stitle>Stoch Environ Res Risk Assess</stitle><date>2024-04-01</date><risdate>2024</risdate><volume>38</volume><issue>4</issue><spage>1403</spage><epage>1422</epage><pages>1403-1422</pages><issn>1436-3240</issn><eissn>1436-3259</eissn><abstract>In this study, we evaluated extreme climate indicators for precipitation and temperature in the Brazilian Legal Amazon (BLA) from 1961 to 2021. Data from 38 National Institute of Meteorology (INMET) weather stations with a record failure rate less than 12% were used, and RClimDex software and the Mann–Kendall test, Pettitt test, standard normal homogeneity test (SNHT), and Buishand test were employed to analyse the data. The results showed increased extreme rainfall events, including the annual total rainfall divided by wet days (SDII). More frequent discontinuities were observed in the 1980s (SNHT) and 1990s (Pettitt and Buishand tests). The extreme temperature climate indicators also significantly increased, particularly in the 1990s. These increases are likely linked to changes in local climate conditions due to agricultural expansion, intensified industrial activities, and regional urbanization. This study underscores the need for proactive measures to curb illegal deforestation and reduce CO
2
emissions and further research to better understand and mitigate the adverse impacts of these changes on the BLA environment and local communities.
Graphical abstract</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1007/s00477-023-02634-7</doi><tpages>20</tpages><orcidid>https://orcid.org/0000-0002-5773-7842</orcidid><orcidid>https://orcid.org/0000-0003-4461-2570</orcidid><orcidid>https://orcid.org/0000-0002-8438-2055</orcidid><orcidid>https://orcid.org/0000-0002-8184-0348</orcidid><orcidid>https://orcid.org/0000-0002-8082-5963</orcidid><orcidid>https://orcid.org/0000-0001-8589-7301</orcidid><orcidid>https://orcid.org/0000-0002-2583-5245</orcidid><orcidid>https://orcid.org/0000-0001-9751-5884</orcidid></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1436-3240 |
| ispartof | Stochastic environmental research and risk assessment, 2024-04, Vol.38 (4), p.1403-1422 |
| issn | 1436-3240 1436-3259 |
| language | eng |
| recordid | cdi_proquest_journals_2983468369 |
| source | Springer Link |
| subjects | Agricultural expansion Aquatic Pollution Biodiversity Carbon dioxide Carbon dioxide emissions Chemistry and Earth Sciences Climate Climate change Climatic conditions Computational Intelligence Computer Science Deforestation Earth and Environmental Science Earth Sciences Ecosystems Environment Environmental research Extreme values Extreme weather Forests Homogeneity Indicators Industrial areas Local communities Math. Appl. in Environmental Science Meteorology Missing data Original Paper Physics Precipitation Probability Theory and Stochastic Processes Rain Rainfall Risk assessment Statistics for Engineering Time series Trends Urbanization Waste Water Technology Water Management Water Pollution Control Weather stations |
| title | Exploring climate extremes in Brazil’s Legal Amazon |
| url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-26T13%3A27%3A01IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Exploring%20climate%20extremes%20in%20Brazil%E2%80%99s%20Legal%20Amazon&rft.jtitle=Stochastic%20environmental%20research%20and%20risk%20assessment&rft.au=de%20Bodas%20Terassi,%20Paulo%20Miguel&rft.date=2024-04-01&rft.volume=38&rft.issue=4&rft.spage=1403&rft.epage=1422&rft.pages=1403-1422&rft.issn=1436-3240&rft.eissn=1436-3259&rft_id=info:doi/10.1007/s00477-023-02634-7&rft_dat=%3Cproquest_cross%3E2983468369%3C/proquest_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c270t-a8d7264b0200acf05d95ad2a1064e016f82f5a91a41ec5082531eab615a2d4e3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2983468369&rft_id=info:pmid/&rfr_iscdi=true |