Decadal and Multidecadal Variability in ERSSTv5 Global SST during 1879–2018
Decadal and multidecadal variability in the ERSSTv5 global SST dataset are studied in terms of implicit fast (noise) and slow (signal) processes that affect variability on decadal time scales. Using a new method that better estimates the fast, or noise, component of decadal variability, estimates of...
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Veröffentlicht in: | Journal of climate 2021-09, Vol.34 (18), p.7461-7473 |
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description | Decadal and multidecadal variability in the ERSSTv5 global SST dataset are studied in terms of implicit fast (noise) and slow (signal) processes that affect variability on decadal time scales. Using a new method that better estimates the fast, or noise, component of decadal variability, estimates of the modes of variability in the slow component are possible. The fast component of decadal variability has a leading fast mode, which explains 62% of the variance, and it is shown that this fast variability, or decadal climate noise, is well represented by any of the indices associated with intradecadal or interannual variability in the tropical Pacific Ocean. Three slow modes are identified, representing 69% of the slow multidecadal variance, after removing the radiative forcing trend. These modes are shown to be related to variability in the Atlantic multidecadal oscillation (AMO) and SST multidecadal variability in the central western Pacific and in the Indian Ocean gyre region, respectively. The first and third slow modes represent two phases of a propagating mode with a period of about 80 years. The second slow mode represents multidecadal variability of the western Pacific warm pool, which is less robust than the other two and shown to be weakly related to the AMO with a lag of about 30 years; fast variability in this region is related to the leading fast mode. Three regions of significant slow variability are identified south of Australia, south of Africa, and near the Drake Passage in association with the Antarctic Circumpolar Current. |
doi_str_mv | 10.1175/JCLI-D-20-0902.1 |
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Using a new method that better estimates the fast, or noise, component of decadal variability, estimates of the modes of variability in the slow component are possible. The fast component of decadal variability has a leading fast mode, which explains 62% of the variance, and it is shown that this fast variability, or decadal climate noise, is well represented by any of the indices associated with intradecadal or interannual variability in the tropical Pacific Ocean. Three slow modes are identified, representing 69% of the slow multidecadal variance, after removing the radiative forcing trend. These modes are shown to be related to variability in the Atlantic multidecadal oscillation (AMO) and SST multidecadal variability in the central western Pacific and in the Indian Ocean gyre region, respectively. The first and third slow modes represent two phases of a propagating mode with a period of about 80 years. The second slow mode represents multidecadal variability of the western Pacific warm pool, which is less robust than the other two and shown to be weakly related to the AMO with a lag of about 30 years; fast variability in this region is related to the leading fast mode. 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Using a new method that better estimates the fast, or noise, component of decadal variability, estimates of the modes of variability in the slow component are possible. The fast component of decadal variability has a leading fast mode, which explains 62% of the variance, and it is shown that this fast variability, or decadal climate noise, is well represented by any of the indices associated with intradecadal or interannual variability in the tropical Pacific Ocean. Three slow modes are identified, representing 69% of the slow multidecadal variance, after removing the radiative forcing trend. These modes are shown to be related to variability in the Atlantic multidecadal oscillation (AMO) and SST multidecadal variability in the central western Pacific and in the Indian Ocean gyre region, respectively. The first and third slow modes represent two phases of a propagating mode with a period of about 80 years. The second slow mode represents multidecadal variability of the western Pacific warm pool, which is less robust than the other two and shown to be weakly related to the AMO with a lag of about 30 years; fast variability in this region is related to the leading fast mode. Three regions of significant slow variability are identified south of Australia, south of Africa, and near the Drake Passage in association with the Antarctic Circumpolar Current.</description><subject>Antarctic Circumpolar Current</subject><subject>Atlantic Oscillation</subject><subject>Estimates</subject><subject>Global temperatures</subject><subject>Identification</subject><subject>Interannual variability</subject><subject>Modes</subject><subject>Noise</subject><subject>Oceans</subject><subject>Propagation modes</subject><subject>Radiative forcing</subject><subject>Sea surface</subject><subject>Signal processing</subject><subject>Tropical climate</subject><subject>Variability</subject><issn>0894-8755</issn><issn>1520-0442</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNo9UE1Lw0AQXUTBWr17EQKet85usl9HaWuttAi2el02m42kxKRuEqE3_4P_0F_ihhRhYHhv3pthHkLXBCaECHb3NF0t8QxTwKCATsgJGhHWoyShp2gEUiVYCsbO0UXT7AAI5QAjtJ45azJTRqbKonVXtkV2JN6ML0xalEV7iIoqmr9sNtsvFi3KOg3TAKKs80X1HhEp1O_3DwUiL9FZbsrGXR37GL0-zLfTR7x6Xiyn9ytsqYpbrMBwl0NiaG4tF7lyUnAqpSE2pdwJkzsO0ljOnAmEShlkwHkOQGnMSBaP0e2wd-_rz841rd7Vna_CSU25YKGU5EEFg8r6umm8y_XeFx_GHzQB3Yem-9D0TFPQfWiaBMvNYNk1be3_9VSAEOG_-A_p_2ce</recordid><startdate>20210901</startdate><enddate>20210901</enddate><creator>Frederiksen, Carsten S.</creator><creator>Zheng, Xiaogu</creator><creator>Grainger, Simon</creator><general>American Meteorological Society</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7QH</scope><scope>7TG</scope><scope>7UA</scope><scope>C1K</scope><scope>F1W</scope><scope>H96</scope><scope>KL.</scope><scope>L.G</scope></search><sort><creationdate>20210901</creationdate><title>Decadal and Multidecadal Variability in ERSSTv5 Global SST during 1879–2018</title><author>Frederiksen, Carsten S. ; Zheng, Xiaogu ; Grainger, Simon</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c293t-90a6ef04a2fcc67f9e876288a1cb26e7afe608ac65eab269b50d066f0022351d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Antarctic Circumpolar Current</topic><topic>Atlantic Oscillation</topic><topic>Estimates</topic><topic>Global temperatures</topic><topic>Identification</topic><topic>Interannual variability</topic><topic>Modes</topic><topic>Noise</topic><topic>Oceans</topic><topic>Propagation modes</topic><topic>Radiative forcing</topic><topic>Sea surface</topic><topic>Signal processing</topic><topic>Tropical climate</topic><topic>Variability</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Frederiksen, Carsten S.</creatorcontrib><creatorcontrib>Zheng, Xiaogu</creatorcontrib><creatorcontrib>Grainger, Simon</creatorcontrib><collection>CrossRef</collection><collection>Aqualine</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><jtitle>Journal of climate</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Frederiksen, Carsten S.</au><au>Zheng, Xiaogu</au><au>Grainger, Simon</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Decadal and Multidecadal Variability in ERSSTv5 Global SST during 1879–2018</atitle><jtitle>Journal of climate</jtitle><date>2021-09-01</date><risdate>2021</risdate><volume>34</volume><issue>18</issue><spage>7461</spage><epage>7473</epage><pages>7461-7473</pages><issn>0894-8755</issn><eissn>1520-0442</eissn><abstract>Decadal and multidecadal variability in the ERSSTv5 global SST dataset are studied in terms of implicit fast (noise) and slow (signal) processes that affect variability on decadal time scales. Using a new method that better estimates the fast, or noise, component of decadal variability, estimates of the modes of variability in the slow component are possible. The fast component of decadal variability has a leading fast mode, which explains 62% of the variance, and it is shown that this fast variability, or decadal climate noise, is well represented by any of the indices associated with intradecadal or interannual variability in the tropical Pacific Ocean. Three slow modes are identified, representing 69% of the slow multidecadal variance, after removing the radiative forcing trend. These modes are shown to be related to variability in the Atlantic multidecadal oscillation (AMO) and SST multidecadal variability in the central western Pacific and in the Indian Ocean gyre region, respectively. The first and third slow modes represent two phases of a propagating mode with a period of about 80 years. The second slow mode represents multidecadal variability of the western Pacific warm pool, which is less robust than the other two and shown to be weakly related to the AMO with a lag of about 30 years; fast variability in this region is related to the leading fast mode. Three regions of significant slow variability are identified south of Australia, south of Africa, and near the Drake Passage in association with the Antarctic Circumpolar Current.</abstract><cop>Boston</cop><pub>American Meteorological Society</pub><doi>10.1175/JCLI-D-20-0902.1</doi><tpages>13</tpages></addata></record> |
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subjects | Antarctic Circumpolar Current Atlantic Oscillation Estimates Global temperatures Identification Interannual variability Modes Noise Oceans Propagation modes Radiative forcing Sea surface Signal processing Tropical climate Variability |
title | Decadal and Multidecadal Variability in ERSSTv5 Global SST during 1879–2018 |
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