Niño4 as a Key Region for the Interannual Variability of the Western Pacific Warm Pool
The Western Pacific Warm Pool (WPWP) plays an important role in the global climate through modulating deep convections, ENSO, monsoon onsets, etc. Due to the vast spatial range and huge heat storage of the WPWP, near‐real‐time monitoring of its three‐dimensional variations remains challenging. Based...
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Veröffentlicht in: | Journal of geophysical research. Oceans 2017-11, Vol.122 (11), p.9299-9314 |
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description | The Western Pacific Warm Pool (WPWP) plays an important role in the global climate through modulating deep convections, ENSO, monsoon onsets, etc. Due to the vast spatial range and huge heat storage of the WPWP, near‐real‐time monitoring of its three‐dimensional variations remains challenging. Based on Argo observations and three reanalysis data sets, we find that the Niño4 sea surface temperature (SST) index captures the interannual variability of the WPWP well. The Niño4 SST can explain approximately half of the variance of the WPWP heat content and almost all the variance of the east‐west migration of the WPWP. An assessment of 31 CMIP5 models also reveals that models with larger interannual spectral powers and amplitudes of the Niño4 SST tend to simulate larger variations in the heat content and east‐west migration of the WPWP. A surface heat budget analysis further shows that the Niño4 SST and WPWP are physically connected through basin‐scale horizontal advections of mean temperatures by anomalous horizontal currents, which dominate the interannual variations of both the Niño4 SST and WPWP. Our results indicate that the Niño4 SST can efficiently estimate the interannual WPWP changes and a reliable predictor of the onset time of the South China Sea summer monsoon and Bay of Bengal summer monsoon, without the need to calculate the eastern boundary location and heat content of the WPWP. Moreover, a better simulation of the SST and horizontal currents in the Niño4 region can help to reduce model bias when reproducing the WPWP's interannual variabilities.
Key Points
The Niño4 SST serves as an efficient estimator to evaluate the interannual variabilities of the heat content and zonal migration of WPWP
Intermodel differences in the interannual variability of the WPWP are significantly coupled with those of the Niño4 SST
The Niño4 SST index is more convenient for representing the WPWP's zonal migration and qualitatively predicting the SCSSM and BOBSM onsets |
doi_str_mv | 10.1002/2017JC013208 |
format | Article |
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Key Points
The Niño4 SST serves as an efficient estimator to evaluate the interannual variabilities of the heat content and zonal migration of WPWP
Intermodel differences in the interannual variability of the WPWP are significantly coupled with those of the Niño4 SST
The Niño4 SST index is more convenient for representing the WPWP's zonal migration and qualitatively predicting the SCSSM and BOBSM onsets</description><identifier>ISSN: 2169-9275</identifier><identifier>EISSN: 2169-9291</identifier><identifier>DOI: 10.1002/2017JC013208</identifier><language>eng</language><publisher>Washington: Blackwell Publishing Ltd</publisher><subject>Annual variations ; Climate models ; CMIP5 models ; Computer simulation ; El Nino ; El Nino phenomena ; El Nino-Southern Oscillation event ; Enthalpy ; Geophysics ; Global climate ; Heat ; Heat budget ; Heat content ; Heat storage ; Interannual variability ; Interannual variations ; Mean temperatures ; Migration ; Monsoons ; Niño4 ; Sea surface ; Sea surface temperature ; Southern Oscillation ; Summer ; Summer monsoon ; Surface temperature ; Variability ; Variance analysis ; Variation ; Western Pacific Warm Pool ; Wind</subject><ispartof>Journal of geophysical research. Oceans, 2017-11, Vol.122 (11), p.9299-9314</ispartof><rights>2017. American Geophysical Union. All Rights Reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a3686-a94a9f01048c51bac8cd3d1444f99fdc3bbae45ccdd55ca736a346cf9280d2523</citedby><cites>FETCH-LOGICAL-a3686-a94a9f01048c51bac8cd3d1444f99fdc3bbae45ccdd55ca736a346cf9280d2523</cites><orcidid>0000-0001-5073-3411 ; 0000-0002-6142-7441</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2F2017JC013208$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2F2017JC013208$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,780,784,1417,1433,27924,27925,45574,45575,46409,46833</link.rule.ids></links><search><creatorcontrib>Jia, Fan</creatorcontrib><creatorcontrib>Hu, Dunxin</creatorcontrib><creatorcontrib>Hu, Shijian</creatorcontrib><creatorcontrib>Feng, Junqiao</creatorcontrib><title>Niño4 as a Key Region for the Interannual Variability of the Western Pacific Warm Pool</title><title>Journal of geophysical research. Oceans</title><description>The Western Pacific Warm Pool (WPWP) plays an important role in the global climate through modulating deep convections, ENSO, monsoon onsets, etc. Due to the vast spatial range and huge heat storage of the WPWP, near‐real‐time monitoring of its three‐dimensional variations remains challenging. Based on Argo observations and three reanalysis data sets, we find that the Niño4 sea surface temperature (SST) index captures the interannual variability of the WPWP well. The Niño4 SST can explain approximately half of the variance of the WPWP heat content and almost all the variance of the east‐west migration of the WPWP. An assessment of 31 CMIP5 models also reveals that models with larger interannual spectral powers and amplitudes of the Niño4 SST tend to simulate larger variations in the heat content and east‐west migration of the WPWP. A surface heat budget analysis further shows that the Niño4 SST and WPWP are physically connected through basin‐scale horizontal advections of mean temperatures by anomalous horizontal currents, which dominate the interannual variations of both the Niño4 SST and WPWP. Our results indicate that the Niño4 SST can efficiently estimate the interannual WPWP changes and a reliable predictor of the onset time of the South China Sea summer monsoon and Bay of Bengal summer monsoon, without the need to calculate the eastern boundary location and heat content of the WPWP. Moreover, a better simulation of the SST and horizontal currents in the Niño4 region can help to reduce model bias when reproducing the WPWP's interannual variabilities.
Key Points
The Niño4 SST serves as an efficient estimator to evaluate the interannual variabilities of the heat content and zonal migration of WPWP
Intermodel differences in the interannual variability of the WPWP are significantly coupled with those of the Niño4 SST
The Niño4 SST index is more convenient for representing the WPWP's zonal migration and qualitatively predicting the SCSSM and BOBSM onsets</description><subject>Annual variations</subject><subject>Climate models</subject><subject>CMIP5 models</subject><subject>Computer simulation</subject><subject>El Nino</subject><subject>El Nino phenomena</subject><subject>El Nino-Southern Oscillation event</subject><subject>Enthalpy</subject><subject>Geophysics</subject><subject>Global climate</subject><subject>Heat</subject><subject>Heat budget</subject><subject>Heat content</subject><subject>Heat storage</subject><subject>Interannual variability</subject><subject>Interannual variations</subject><subject>Mean temperatures</subject><subject>Migration</subject><subject>Monsoons</subject><subject>Niño4</subject><subject>Sea surface</subject><subject>Sea surface temperature</subject><subject>Southern Oscillation</subject><subject>Summer</subject><subject>Summer monsoon</subject><subject>Surface temperature</subject><subject>Variability</subject><subject>Variance analysis</subject><subject>Variation</subject><subject>Western Pacific Warm Pool</subject><subject>Wind</subject><issn>2169-9275</issn><issn>2169-9291</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><recordid>eNp9kM1Kw0AUhQdRsFR3PsCAW6Pzm8wsJWhtLVqK2mW4mczolDRTJy2Sx_IZfDGjFXHl3dwL5-Ocy0HohJJzSgi7YIRmk5xQzojaQwNGU51opun-753JQ3TctkvSj6JKCD1Aizv_8R4EhhYDvrUdnttnHxrsQsSbF4vHzcZGaJot1PgJoofS137T4eC-5YVte73BMzDeeYMXEFd4FkJ9hA4c1K09_tlD9Hh99ZDfJNP70Ti_nCbAU5UmoAVoRygRykhaglGm4hUVQjitXWV4WYIV0piqktJAxlPgIjVOM0UqJhkfotOd7zqG123_TbEM29j0kQXVWcpVxrTsqbMdZWJo22hdsY5-BbErKCm-2iv-ttfjfIe_-dp2_7LFZDTPGZMq5Z9lVW--</recordid><startdate>201711</startdate><enddate>201711</enddate><creator>Jia, Fan</creator><creator>Hu, Dunxin</creator><creator>Hu, Shijian</creator><creator>Feng, Junqiao</creator><general>Blackwell Publishing Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7TG</scope><scope>7TN</scope><scope>F1W</scope><scope>H96</scope><scope>KL.</scope><scope>L.G</scope><orcidid>https://orcid.org/0000-0001-5073-3411</orcidid><orcidid>https://orcid.org/0000-0002-6142-7441</orcidid></search><sort><creationdate>201711</creationdate><title>Niño4 as a Key Region for the Interannual Variability of the Western Pacific Warm Pool</title><author>Jia, Fan ; Hu, Dunxin ; Hu, Shijian ; Feng, Junqiao</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a3686-a94a9f01048c51bac8cd3d1444f99fdc3bbae45ccdd55ca736a346cf9280d2523</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Annual variations</topic><topic>Climate models</topic><topic>CMIP5 models</topic><topic>Computer simulation</topic><topic>El Nino</topic><topic>El Nino phenomena</topic><topic>El Nino-Southern Oscillation event</topic><topic>Enthalpy</topic><topic>Geophysics</topic><topic>Global climate</topic><topic>Heat</topic><topic>Heat budget</topic><topic>Heat content</topic><topic>Heat storage</topic><topic>Interannual variability</topic><topic>Interannual variations</topic><topic>Mean temperatures</topic><topic>Migration</topic><topic>Monsoons</topic><topic>Niño4</topic><topic>Sea surface</topic><topic>Sea surface temperature</topic><topic>Southern Oscillation</topic><topic>Summer</topic><topic>Summer monsoon</topic><topic>Surface temperature</topic><topic>Variability</topic><topic>Variance analysis</topic><topic>Variation</topic><topic>Western Pacific Warm Pool</topic><topic>Wind</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Jia, Fan</creatorcontrib><creatorcontrib>Hu, Dunxin</creatorcontrib><creatorcontrib>Hu, Shijian</creatorcontrib><creatorcontrib>Feng, Junqiao</creatorcontrib><collection>CrossRef</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Oceanic Abstracts</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 geophysical research. Oceans</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Jia, Fan</au><au>Hu, Dunxin</au><au>Hu, Shijian</au><au>Feng, Junqiao</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Niño4 as a Key Region for the Interannual Variability of the Western Pacific Warm Pool</atitle><jtitle>Journal of geophysical research. Oceans</jtitle><date>2017-11</date><risdate>2017</risdate><volume>122</volume><issue>11</issue><spage>9299</spage><epage>9314</epage><pages>9299-9314</pages><issn>2169-9275</issn><eissn>2169-9291</eissn><abstract>The Western Pacific Warm Pool (WPWP) plays an important role in the global climate through modulating deep convections, ENSO, monsoon onsets, etc. Due to the vast spatial range and huge heat storage of the WPWP, near‐real‐time monitoring of its three‐dimensional variations remains challenging. Based on Argo observations and three reanalysis data sets, we find that the Niño4 sea surface temperature (SST) index captures the interannual variability of the WPWP well. The Niño4 SST can explain approximately half of the variance of the WPWP heat content and almost all the variance of the east‐west migration of the WPWP. An assessment of 31 CMIP5 models also reveals that models with larger interannual spectral powers and amplitudes of the Niño4 SST tend to simulate larger variations in the heat content and east‐west migration of the WPWP. A surface heat budget analysis further shows that the Niño4 SST and WPWP are physically connected through basin‐scale horizontal advections of mean temperatures by anomalous horizontal currents, which dominate the interannual variations of both the Niño4 SST and WPWP. Our results indicate that the Niño4 SST can efficiently estimate the interannual WPWP changes and a reliable predictor of the onset time of the South China Sea summer monsoon and Bay of Bengal summer monsoon, without the need to calculate the eastern boundary location and heat content of the WPWP. Moreover, a better simulation of the SST and horizontal currents in the Niño4 region can help to reduce model bias when reproducing the WPWP's interannual variabilities.
Key Points
The Niño4 SST serves as an efficient estimator to evaluate the interannual variabilities of the heat content and zonal migration of WPWP
Intermodel differences in the interannual variability of the WPWP are significantly coupled with those of the Niño4 SST
The Niño4 SST index is more convenient for representing the WPWP's zonal migration and qualitatively predicting the SCSSM and BOBSM onsets</abstract><cop>Washington</cop><pub>Blackwell Publishing Ltd</pub><doi>10.1002/2017JC013208</doi><tpages>16</tpages><orcidid>https://orcid.org/0000-0001-5073-3411</orcidid><orcidid>https://orcid.org/0000-0002-6142-7441</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Annual variations Climate models CMIP5 models Computer simulation El Nino El Nino phenomena El Nino-Southern Oscillation event Enthalpy Geophysics Global climate Heat Heat budget Heat content Heat storage Interannual variability Interannual variations Mean temperatures Migration Monsoons Niño4 Sea surface Sea surface temperature Southern Oscillation Summer Summer monsoon Surface temperature Variability Variance analysis Variation Western Pacific Warm Pool Wind |
title | Niño4 as a Key Region for the Interannual Variability of the Western Pacific Warm Pool |
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