The relationship between ENSO, IOD and SAM with extreme rainfall over South America
There is growing acceptance that the climate is changing. The Intergovernmental Panel on Climate Change reports that extreme events are accentuated with climate change, contributing to the risk and vulnerability of social and environmental systems. This research is focused on South America analyzing...
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Veröffentlicht in: | Stochastic environmental research and risk assessment 2024-05, Vol.38 (5), p.1769-1782 |
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description | There is growing acceptance that the climate is changing. The Intergovernmental Panel on Climate Change reports that extreme events are accentuated with climate change, contributing to the risk and vulnerability of social and environmental systems. This research is focused on South America analyzing the spatial distribution of rainfall and extreme rainfall indices. Then, the pattern of influence of El Niño-Southern Oscillation (ENSO), the Southern Annular Mode (SAM) and the Indian Ocean Dipole (IOD) forcings were analyzed. The climate analysis of the indices highlights the spatial coherence between them over the wettest and driest subregions. Lower total accumulated rainfall, number of rainy days, total accumulated rainfall due to moderate wet days, maximum number of consecutive wet days and higher maximum number of consecutive dry days were observed in the northeast of Brazil, the southeast of Argentina and the Andean region. The opposite was observed in Amazonia and Southeastern South America (SESA).Three subregions were analyzed: north of South America (NSA), South Atlantic Convergence Zone (SACZ), and SESA; being the ENSO events, the ones that provide a stronger and more spatially distributed signal. While the IOD signal is similar when analyzing on a monthly basis, SAM gets deeper in November. In general, the signal in SACZ shows greater spatial variability, while in NSA contains the largest number of significant grid points of opposite sign to the SESA. The response of rainfall and rainfall extreme events to ENSO, SAM and IOD forcings provides useful information for climate services, especially in global warming scenario. |
doi_str_mv | 10.1007/s00477-023-02653-4 |
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The Intergovernmental Panel on Climate Change reports that extreme events are accentuated with climate change, contributing to the risk and vulnerability of social and environmental systems. This research is focused on South America analyzing the spatial distribution of rainfall and extreme rainfall indices. Then, the pattern of influence of El Niño-Southern Oscillation (ENSO), the Southern Annular Mode (SAM) and the Indian Ocean Dipole (IOD) forcings were analyzed. The climate analysis of the indices highlights the spatial coherence between them over the wettest and driest subregions. Lower total accumulated rainfall, number of rainy days, total accumulated rainfall due to moderate wet days, maximum number of consecutive wet days and higher maximum number of consecutive dry days were observed in the northeast of Brazil, the southeast of Argentina and the Andean region. The opposite was observed in Amazonia and Southeastern South America (SESA).Three subregions were analyzed: north of South America (NSA), South Atlantic Convergence Zone (SACZ), and SESA; being the ENSO events, the ones that provide a stronger and more spatially distributed signal. While the IOD signal is similar when analyzing on a monthly basis, SAM gets deeper in November. In general, the signal in SACZ shows greater spatial variability, while in NSA contains the largest number of significant grid points of opposite sign to the SESA. 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The Intergovernmental Panel on Climate Change reports that extreme events are accentuated with climate change, contributing to the risk and vulnerability of social and environmental systems. This research is focused on South America analyzing the spatial distribution of rainfall and extreme rainfall indices. Then, the pattern of influence of El Niño-Southern Oscillation (ENSO), the Southern Annular Mode (SAM) and the Indian Ocean Dipole (IOD) forcings were analyzed. The climate analysis of the indices highlights the spatial coherence between them over the wettest and driest subregions. Lower total accumulated rainfall, number of rainy days, total accumulated rainfall due to moderate wet days, maximum number of consecutive wet days and higher maximum number of consecutive dry days were observed in the northeast of Brazil, the southeast of Argentina and the Andean region. The opposite was observed in Amazonia and Southeastern South America (SESA).Three subregions were analyzed: north of South America (NSA), South Atlantic Convergence Zone (SACZ), and SESA; being the ENSO events, the ones that provide a stronger and more spatially distributed signal. While the IOD signal is similar when analyzing on a monthly basis, SAM gets deeper in November. In general, the signal in SACZ shows greater spatial variability, while in NSA contains the largest number of significant grid points of opposite sign to the SESA. The response of rainfall and rainfall extreme events to ENSO, SAM and IOD forcings provides useful information for climate services, especially in global warming scenario.</description><subject>Aquatic Pollution</subject><subject>Chemistry and Earth Sciences</subject><subject>Climate change</subject><subject>Computational Intelligence</subject><subject>Computer Science</subject><subject>Dipoles</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>El Nino</subject><subject>Environment</subject><subject>Extreme weather</subject><subject>Global warming</subject><subject>Intergovernmental Panel on Climate Change</subject><subject>Math. Appl. in Environmental Science</subject><subject>Original Paper</subject><subject>Physics</subject><subject>Probability Theory and Stochastic Processes</subject><subject>Rainfall</subject><subject>Southern Oscillation</subject><subject>Spatial distribution</subject><subject>Statistics for Engineering</subject><subject>Waste Water Technology</subject><subject>Water Management</subject><subject>Water Pollution Control</subject><issn>1436-3240</issn><issn>1436-3259</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNp9kD1PwzAQhi0EEqXwB5gssRI4f9djVQpUAjqkzJYTOzRVmxQ7pfDvMQTBxnC6k96Pkx6EzglcEQB1HQG4UhlQlkYKlvEDNCCcyYxRoQ9_bw7H6CTGFQBRSvAByhdLj4Nf265um7ist7jw3d77Bk-f8vklns1vsG0czsePeF93S-zfu-A3KWPrprLrNW7ffMB5u0vaeONDXdpTdJSU6M9-9hA9304Xk_vsYX43m4wfspIq6LKRKqR0VAtaVU5SsFoDKUbKMiicKwsnrBSCO8Et19oqb60uCCdEM-pAUDZEF33vNrSvOx87s2p3oUkvDQOuQUhgKrlo7ypDG2PwldmGemPDhyFgvuCZHp5J8Mw3PMNTiPWhmMzNiw9_1f-kPgGR0nAZ</recordid><startdate>20240501</startdate><enddate>20240501</enddate><creator>Iacovone, Maria Florencia</creator><creator>Pántano, Vanesa C.</creator><creator>Penalba, Olga C.</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/0000-0002-6123-3364</orcidid></search><sort><creationdate>20240501</creationdate><title>The relationship between ENSO, IOD and SAM with extreme rainfall over South America</title><author>Iacovone, Maria Florencia ; Pántano, Vanesa C. ; Penalba, Olga C.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c270t-87b66d2952ffd620a9901b87a30bddcbd5a6554d54a499a7eaa9b1411932d0523</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Aquatic Pollution</topic><topic>Chemistry and Earth Sciences</topic><topic>Climate change</topic><topic>Computational Intelligence</topic><topic>Computer Science</topic><topic>Dipoles</topic><topic>Earth and Environmental Science</topic><topic>Earth Sciences</topic><topic>El Nino</topic><topic>Environment</topic><topic>Extreme weather</topic><topic>Global warming</topic><topic>Intergovernmental Panel on Climate Change</topic><topic>Math. Appl. in Environmental Science</topic><topic>Original Paper</topic><topic>Physics</topic><topic>Probability Theory and Stochastic Processes</topic><topic>Rainfall</topic><topic>Southern Oscillation</topic><topic>Spatial distribution</topic><topic>Statistics for Engineering</topic><topic>Waste Water Technology</topic><topic>Water Management</topic><topic>Water Pollution Control</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Iacovone, Maria Florencia</creatorcontrib><creatorcontrib>Pántano, Vanesa C.</creatorcontrib><creatorcontrib>Penalba, Olga C.</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>Iacovone, Maria Florencia</au><au>Pántano, Vanesa C.</au><au>Penalba, Olga C.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The relationship between ENSO, IOD and SAM with extreme rainfall over South America</atitle><jtitle>Stochastic environmental research and risk assessment</jtitle><stitle>Stoch Environ Res Risk Assess</stitle><date>2024-05-01</date><risdate>2024</risdate><volume>38</volume><issue>5</issue><spage>1769</spage><epage>1782</epage><pages>1769-1782</pages><issn>1436-3240</issn><eissn>1436-3259</eissn><abstract>There is growing acceptance that the climate is changing. The Intergovernmental Panel on Climate Change reports that extreme events are accentuated with climate change, contributing to the risk and vulnerability of social and environmental systems. This research is focused on South America analyzing the spatial distribution of rainfall and extreme rainfall indices. Then, the pattern of influence of El Niño-Southern Oscillation (ENSO), the Southern Annular Mode (SAM) and the Indian Ocean Dipole (IOD) forcings were analyzed. The climate analysis of the indices highlights the spatial coherence between them over the wettest and driest subregions. Lower total accumulated rainfall, number of rainy days, total accumulated rainfall due to moderate wet days, maximum number of consecutive wet days and higher maximum number of consecutive dry days were observed in the northeast of Brazil, the southeast of Argentina and the Andean region. The opposite was observed in Amazonia and Southeastern South America (SESA).Three subregions were analyzed: north of South America (NSA), South Atlantic Convergence Zone (SACZ), and SESA; being the ENSO events, the ones that provide a stronger and more spatially distributed signal. While the IOD signal is similar when analyzing on a monthly basis, SAM gets deeper in November. In general, the signal in SACZ shows greater spatial variability, while in NSA contains the largest number of significant grid points of opposite sign to the SESA. The response of rainfall and rainfall extreme events to ENSO, SAM and IOD forcings provides useful information for climate services, especially in global warming scenario.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1007/s00477-023-02653-4</doi><tpages>14</tpages><orcidid>https://orcid.org/0000-0002-6123-3364</orcidid></addata></record> |
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subjects | Aquatic Pollution Chemistry and Earth Sciences Climate change Computational Intelligence Computer Science Dipoles Earth and Environmental Science Earth Sciences El Nino Environment Extreme weather Global warming Intergovernmental Panel on Climate Change Math. Appl. in Environmental Science Original Paper Physics Probability Theory and Stochastic Processes Rainfall Southern Oscillation Spatial distribution Statistics for Engineering Waste Water Technology Water Management Water Pollution Control |
title | The relationship between ENSO, IOD and SAM with extreme rainfall over South America |
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