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Indian summer monsoon rainfall variability in global coupled ocean-atmospheric models
Performance of seven fully coupled models in simulating Indian summer monsoon climatology as well as the inter-annual variability was assessed using multi member 1 month lead hindcasts made by several European climate groups as part of the program called Development of a European multi-model ensembl...
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Published in: | Climate dynamics 2010-12, Vol.35 (7-8), p.1521-1539 |
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description | Performance of seven fully coupled models in simulating Indian summer monsoon climatology as well as the inter-annual variability was assessed using multi member 1 month lead hindcasts made by several European climate groups as part of the program called Development of a European multi-model ensemble system for seasonal-to-inter-annual prediction (DEMETER). Dependency of the model simulated Indian summer monsoon rainfall and global sea surface temperatures on model formulation and initial conditions have been studied in detail using the nine ensemble member simulations of the seven different coupled ocean-atmosphere models participated in the DEMETER program. It was found that the skills of the monsoon predictions in these hindcasts are generally positive though they are very modest. Model simulations of India summer monsoon rainfall for the earlier period (1959-1979) are closer to the ‘perfect model' (attainable) score but, large differences are observed between ‘actual' skill and ‘perfect model' skill in the recent period (1980-2001). Spread among the ensemble members are found to be large in simulations of India summer monsoon rainfall (ISMR) and Indian ocean dipole mode (IODM), indicating strong dependency of model simulated Indian summer monsoon on initial conditions. Multi-model ensemble performs better than the individual models in simulating ENSO indices, but does not perform better than the individual models in simulating ISMR and IODM. Decreased skill of multi-model ensemble over the region indicates amplification of errors due to existence of similar errors in the individual models. It appears that large biases in predicted SSTs over Indian Ocean region and the not so perfect ENSO-monsoon (IODM-monsoon) tele-connections are some of the possible reasons for such lower than expected skills in the recent period. The low skill of multi-model ensemble, large spread among the ensemble members of individual models and the not so perfect monsoon tele-connection with global SSTs points towards the importance of improving individual models for better simulation of the Indian monsoon. |
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H ; Krishna Kumar, K</creator><creatorcontrib>Preethi, B ; Kripalani, R. H ; Krishna Kumar, K</creatorcontrib><description>Performance of seven fully coupled models in simulating Indian summer monsoon climatology as well as the inter-annual variability was assessed using multi member 1 month lead hindcasts made by several European climate groups as part of the program called Development of a European multi-model ensemble system for seasonal-to-inter-annual prediction (DEMETER). Dependency of the model simulated Indian summer monsoon rainfall and global sea surface temperatures on model formulation and initial conditions have been studied in detail using the nine ensemble member simulations of the seven different coupled ocean-atmosphere models participated in the DEMETER program. It was found that the skills of the monsoon predictions in these hindcasts are generally positive though they are very modest. Model simulations of India summer monsoon rainfall for the earlier period (1959-1979) are closer to the ‘perfect model' (attainable) score but, large differences are observed between ‘actual' skill and ‘perfect model' skill in the recent period (1980-2001). Spread among the ensemble members are found to be large in simulations of India summer monsoon rainfall (ISMR) and Indian ocean dipole mode (IODM), indicating strong dependency of model simulated Indian summer monsoon on initial conditions. Multi-model ensemble performs better than the individual models in simulating ENSO indices, but does not perform better than the individual models in simulating ISMR and IODM. Decreased skill of multi-model ensemble over the region indicates amplification of errors due to existence of similar errors in the individual models. It appears that large biases in predicted SSTs over Indian Ocean region and the not so perfect ENSO-monsoon (IODM-monsoon) tele-connections are some of the possible reasons for such lower than expected skills in the recent period. The low skill of multi-model ensemble, large spread among the ensemble members of individual models and the not so perfect monsoon tele-connection with global SSTs points towards the importance of improving individual models for better simulation of the Indian monsoon.</description><identifier>ISSN: 0930-7575</identifier><identifier>EISSN: 1432-0894</identifier><identifier>DOI: 10.1007/s00382-009-0657-x</identifier><identifier>CODEN: CLDYEM</identifier><language>eng</language><publisher>Berlin/Heidelberg: Berlin/Heidelberg : Springer-Verlag</publisher><subject>Analysis ; Annual variations ; Atmospheric models ; Climate ; Climatology ; Climatology. Bioclimatology. Climate change ; Earth and Environmental Science ; Earth Sciences ; Earth, ocean, space ; El Nino ; ENSO ; Exact sciences and technology ; External geophysics ; Geophysics/Geodesy ; Global temperatures ; Indian monsoon rainfall ; IODM ; Meteorology ; Monsoons ; Multi-model ensemble ; Ocean ; Ocean currents ; Ocean-atmosphere interaction ; Oceanography ; Precipitation variability ; Rain ; Rain and rainfall ; Rainfall ; Sea surface temperature ; Summer ; Tele-connections</subject><ispartof>Climate dynamics, 2010-12, Vol.35 (7-8), p.1521-1539</ispartof><rights>Springer-Verlag 2009</rights><rights>2015 INIST-CNRS</rights><rights>COPYRIGHT 2010 Springer</rights><rights>Springer-Verlag 2010</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c539t-b8be8d90a7642c26cbecd9e4409015c81d995dff3537c9c69a1b176e4f6f2ad03</citedby><cites>FETCH-LOGICAL-c539t-b8be8d90a7642c26cbecd9e4409015c81d995dff3537c9c69a1b176e4f6f2ad03</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=23459293$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Preethi, B</creatorcontrib><creatorcontrib>Kripalani, R. H</creatorcontrib><creatorcontrib>Krishna Kumar, K</creatorcontrib><title>Indian summer monsoon rainfall variability in global coupled ocean-atmospheric models</title><title>Climate dynamics</title><addtitle>Clim Dyn</addtitle><description>Performance of seven fully coupled models in simulating Indian summer monsoon climatology as well as the inter-annual variability was assessed using multi member 1 month lead hindcasts made by several European climate groups as part of the program called Development of a European multi-model ensemble system for seasonal-to-inter-annual prediction (DEMETER). Dependency of the model simulated Indian summer monsoon rainfall and global sea surface temperatures on model formulation and initial conditions have been studied in detail using the nine ensemble member simulations of the seven different coupled ocean-atmosphere models participated in the DEMETER program. It was found that the skills of the monsoon predictions in these hindcasts are generally positive though they are very modest. Model simulations of India summer monsoon rainfall for the earlier period (1959-1979) are closer to the ‘perfect model' (attainable) score but, large differences are observed between ‘actual' skill and ‘perfect model' skill in the recent period (1980-2001). Spread among the ensemble members are found to be large in simulations of India summer monsoon rainfall (ISMR) and Indian ocean dipole mode (IODM), indicating strong dependency of model simulated Indian summer monsoon on initial conditions. Multi-model ensemble performs better than the individual models in simulating ENSO indices, but does not perform better than the individual models in simulating ISMR and IODM. Decreased skill of multi-model ensemble over the region indicates amplification of errors due to existence of similar errors in the individual models. It appears that large biases in predicted SSTs over Indian Ocean region and the not so perfect ENSO-monsoon (IODM-monsoon) tele-connections are some of the possible reasons for such lower than expected skills in the recent period. The low skill of multi-model ensemble, large spread among the ensemble members of individual models and the not so perfect monsoon tele-connection with global SSTs points towards the importance of improving individual models for better simulation of the Indian monsoon.</description><subject>Analysis</subject><subject>Annual variations</subject><subject>Atmospheric models</subject><subject>Climate</subject><subject>Climatology</subject><subject>Climatology. Bioclimatology. Climate change</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Earth, ocean, space</subject><subject>El Nino</subject><subject>ENSO</subject><subject>Exact sciences and technology</subject><subject>External geophysics</subject><subject>Geophysics/Geodesy</subject><subject>Global temperatures</subject><subject>Indian monsoon rainfall</subject><subject>IODM</subject><subject>Meteorology</subject><subject>Monsoons</subject><subject>Multi-model ensemble</subject><subject>Ocean</subject><subject>Ocean currents</subject><subject>Ocean-atmosphere interaction</subject><subject>Oceanography</subject><subject>Precipitation variability</subject><subject>Rain</subject><subject>Rain and rainfall</subject><subject>Rainfall</subject><subject>Sea surface temperature</subject><subject>Summer</subject><subject>Tele-connections</subject><issn>0930-7575</issn><issn>1432-0894</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2010</creationdate><recordtype>article</recordtype><recordid>eNp9kUFr3DAQhU1podu0P6CnmkIDPTgZWZJtHUNo2oVAIemexViSvQqytJXssvn3VXBou5eig2D0vTeaeUXxnsAFAWgvEwDt6gpAVNDwtjq-KDaE0VzpBHtZbEBQqFre8tfFm5QeAAhr2npT7LZeW_RlWqbJxHIKPoXgy4jWD-hc-Qujxd46Oz-W1pejCz26UoXl4IwugzLoK5ynkA57E63KBtq49LZ4ldXJvHu-z4rdzZcf19-q2-9ft9dXt5XiVMxV3_Wm0wKwbVit6kb1RmlhGAMBhKuOaCG4HgbKaauEagSSnrSNYUMz1KiBnhUfV99DDD8Xk2b5EJboc0vZQTallHYZulihEZ2Rea4wR1T5aDNZFbwZbK5fUc4JB9qyLPh8IsjMbI7ziEtKcnt_d8qe_8PuDbp5n4JbZps3eQqSFVQxpBTNIA_RThgfJQH5FKFcI5Q5QvkUoTxmzafn8TApdENEr2z6I6wp46IWNHP1yqX85EcT_67hf-YfVtGAQeIYs_HuvgZCgQiS_93R38yotAo</recordid><startdate>20101201</startdate><enddate>20101201</enddate><creator>Preethi, B</creator><creator>Kripalani, R. 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H</au><au>Krishna Kumar, K</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Indian summer monsoon rainfall variability in global coupled ocean-atmospheric models</atitle><jtitle>Climate dynamics</jtitle><stitle>Clim Dyn</stitle><date>2010-12-01</date><risdate>2010</risdate><volume>35</volume><issue>7-8</issue><spage>1521</spage><epage>1539</epage><pages>1521-1539</pages><issn>0930-7575</issn><eissn>1432-0894</eissn><coden>CLDYEM</coden><abstract>Performance of seven fully coupled models in simulating Indian summer monsoon climatology as well as the inter-annual variability was assessed using multi member 1 month lead hindcasts made by several European climate groups as part of the program called Development of a European multi-model ensemble system for seasonal-to-inter-annual prediction (DEMETER). Dependency of the model simulated Indian summer monsoon rainfall and global sea surface temperatures on model formulation and initial conditions have been studied in detail using the nine ensemble member simulations of the seven different coupled ocean-atmosphere models participated in the DEMETER program. It was found that the skills of the monsoon predictions in these hindcasts are generally positive though they are very modest. Model simulations of India summer monsoon rainfall for the earlier period (1959-1979) are closer to the ‘perfect model' (attainable) score but, large differences are observed between ‘actual' skill and ‘perfect model' skill in the recent period (1980-2001). Spread among the ensemble members are found to be large in simulations of India summer monsoon rainfall (ISMR) and Indian ocean dipole mode (IODM), indicating strong dependency of model simulated Indian summer monsoon on initial conditions. Multi-model ensemble performs better than the individual models in simulating ENSO indices, but does not perform better than the individual models in simulating ISMR and IODM. Decreased skill of multi-model ensemble over the region indicates amplification of errors due to existence of similar errors in the individual models. It appears that large biases in predicted SSTs over Indian Ocean region and the not so perfect ENSO-monsoon (IODM-monsoon) tele-connections are some of the possible reasons for such lower than expected skills in the recent period. The low skill of multi-model ensemble, large spread among the ensemble members of individual models and the not so perfect monsoon tele-connection with global SSTs points towards the importance of improving individual models for better simulation of the Indian monsoon.</abstract><cop>Berlin/Heidelberg</cop><pub>Berlin/Heidelberg : Springer-Verlag</pub><doi>10.1007/s00382-009-0657-x</doi><tpages>19</tpages></addata></record> |
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subjects | Analysis Annual variations Atmospheric models Climate Climatology Climatology. Bioclimatology. Climate change Earth and Environmental Science Earth Sciences Earth, ocean, space El Nino ENSO Exact sciences and technology External geophysics Geophysics/Geodesy Global temperatures Indian monsoon rainfall IODM Meteorology Monsoons Multi-model ensemble Ocean Ocean currents Ocean-atmosphere interaction Oceanography Precipitation variability Rain Rain and rainfall Rainfall Sea surface temperature Summer Tele-connections |
title | Indian summer monsoon rainfall variability in global coupled ocean-atmospheric models |
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