Recent Progress in Numerical Atmospheric Modeling in China
This review summarizes the scientific and technical progress in atmospheric modeling in China since 2011, including the dynamical core, model physics, data assimilation, ensemble forecasting, and model evaluation strategies. In terms of the dynamical core, important efforts have been made in the imp...
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Veröffentlicht in: | Advances in atmospheric sciences 2019-09, Vol.36 (9), p.938-960 |
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description | This review summarizes the scientific and technical progress in atmospheric modeling in China since 2011, including the dynamical core, model physics, data assimilation, ensemble forecasting, and model evaluation strategies. In terms of the dynamical core, important efforts have been made in the improvement of the existing model formulations and in exploring new modeling approaches that can better adapt to massively parallel computers and global multiscale modeling. With regard to model physics, various achievements in physical representations have been made, especially a trend toward scale-aware parameterization for accommodating the increase of model resolution. In the field of data assimilation, a 4D-Var system has been developed and is operationally used by the National Meteorological Center of China, and its performance is promising. Furthermore, ensemble forecasting has played a more important role in operational forecast systems and progressed in many fundamental techniques. Model evaluation strategies, including key performance metrics and standardized experimental protocols, have been proposed and widely applied to better understand the strengths and weaknesses of the systems, offering key routes for model improvement. The paper concludes with a concise summary of the status quo and a brief outlook in terms of future development. |
doi_str_mv | 10.1007/s00376-019-8203-1 |
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In terms of the dynamical core, important efforts have been made in the improvement of the existing model formulations and in exploring new modeling approaches that can better adapt to massively parallel computers and global multiscale modeling. With regard to model physics, various achievements in physical representations have been made, especially a trend toward scale-aware parameterization for accommodating the increase of model resolution. In the field of data assimilation, a 4D-Var system has been developed and is operationally used by the National Meteorological Center of China, and its performance is promising. Furthermore, ensemble forecasting has played a more important role in operational forecast systems and progressed in many fundamental techniques. Model evaluation strategies, including key performance metrics and standardized experimental protocols, have been proposed and widely applied to better understand the strengths and weaknesses of the systems, offering key routes for model improvement. The paper concludes with a concise summary of the status quo and a brief outlook in terms of future development.</description><identifier>ISSN: 0256-1530</identifier><identifier>EISSN: 1861-9533</identifier><identifier>DOI: 10.1007/s00376-019-8203-1</identifier><language>eng</language><publisher>Heidelberg: Science Press</publisher><subject>Atmospheric models ; Atmospheric Sciences ; Computer simulation ; Computers ; Data assimilation ; Data collection ; Earth and Environmental Science ; Earth Sciences ; Ensemble forecasting ; Evaluation ; Forecasting ; Formulations ; Geophysics/Geodesy ; Mathematical models ; Meteorology ; Modelling ; National Reports to the IUGG by Chinese National Committee for IAMAS ; Parallel computers ; Parameterization ; Performance measurement ; Physics ; Review</subject><ispartof>Advances in atmospheric sciences, 2019-09, Vol.36 (9), p.938-960</ispartof><rights>Institute of Atmospheric Physics/Chinese Academy of Sciences, and Science Press and Springer-Verlag GmbH Germany, part of Springer Nature 2019</rights><rights>Institute of Atmospheric Physics/Chinese Academy of Sciences, and Science Press and Springer-Verlag GmbH Germany, part of Springer Nature 2019.</rights><rights>Copyright © Wanfang Data Co. 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All Rights Reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c350t-2600d36656a55f26d64a21e9811397ebad0b3ce9a74a5cbc5c6c5b06b8d4101a3</citedby><cites>FETCH-LOGICAL-c350t-2600d36656a55f26d64a21e9811397ebad0b3ce9a74a5cbc5c6c5b06b8d4101a3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Uhttp://www.wanfangdata.com.cn/images/PeriodicalImages/dqkxjz-e/dqkxjz-e.jpg</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s00376-019-8203-1$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00376-019-8203-1$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,41488,42557,51319</link.rule.ids></links><search><creatorcontrib>Yu, Rucong</creatorcontrib><creatorcontrib>Zhang, Yi</creatorcontrib><creatorcontrib>Wang, Jianjie</creatorcontrib><creatorcontrib>Li, Jian</creatorcontrib><creatorcontrib>Chen, Haoming</creatorcontrib><creatorcontrib>Gong, Jiandong</creatorcontrib><creatorcontrib>Chen, Jing</creatorcontrib><title>Recent Progress in Numerical Atmospheric Modeling in China</title><title>Advances in atmospheric sciences</title><addtitle>Adv. Atmos. Sci</addtitle><description>This review summarizes the scientific and technical progress in atmospheric modeling in China since 2011, including the dynamical core, model physics, data assimilation, ensemble forecasting, and model evaluation strategies. In terms of the dynamical core, important efforts have been made in the improvement of the existing model formulations and in exploring new modeling approaches that can better adapt to massively parallel computers and global multiscale modeling. With regard to model physics, various achievements in physical representations have been made, especially a trend toward scale-aware parameterization for accommodating the increase of model resolution. In the field of data assimilation, a 4D-Var system has been developed and is operationally used by the National Meteorological Center of China, and its performance is promising. Furthermore, ensemble forecasting has played a more important role in operational forecast systems and progressed in many fundamental techniques. Model evaluation strategies, including key performance metrics and standardized experimental protocols, have been proposed and widely applied to better understand the strengths and weaknesses of the systems, offering key routes for model improvement. The paper concludes with a concise summary of the status quo and a brief outlook in terms of future development.</description><subject>Atmospheric models</subject><subject>Atmospheric Sciences</subject><subject>Computer simulation</subject><subject>Computers</subject><subject>Data assimilation</subject><subject>Data collection</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Ensemble forecasting</subject><subject>Evaluation</subject><subject>Forecasting</subject><subject>Formulations</subject><subject>Geophysics/Geodesy</subject><subject>Mathematical models</subject><subject>Meteorology</subject><subject>Modelling</subject><subject>National Reports to the IUGG by Chinese National Committee for IAMAS</subject><subject>Parallel computers</subject><subject>Parameterization</subject><subject>Performance measurement</subject><subject>Physics</subject><subject>Review</subject><issn>0256-1530</issn><issn>1861-9533</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><recordid>eNp10M1LwzAYBvAgCs7pH-Ct4MlD9H2TJWm9jeEXzA9EzyFN065zS2fS4cdfb0uFnTyFwO95Qh5CThEuEEBdRgCuJAXMaMqAU9wjI0wl0kxwvk9GwISkKDgckqMYl53OeIojcvXirPNt8hyaKrgYk9onj9u1C7U1q2Tarpu4WfS35KEp3Kr2VS9mi9qbY3JQmlV0J3_nmLzdXL_O7uj86fZ-Np1TywW0lEmAgksppBGiZLKQE8PQZSkiz5TLTQE5ty4zamKEza2w0oocZJ4WEwQ0fEzOh95P40vjK71stsF3L-ri4_1r-aMd674NGYDo7NlgN6H52LrY7jBjgikFSvQKB2VDE2Nwpd6Eem3Ct0bQ_Zx6mFN3vbqfU2OXYUMmdtZXLuya_w_9AsPMdcM</recordid><startdate>20190901</startdate><enddate>20190901</enddate><creator>Yu, Rucong</creator><creator>Zhang, Yi</creator><creator>Wang, Jianjie</creator><creator>Li, Jian</creator><creator>Chen, Haoming</creator><creator>Gong, Jiandong</creator><creator>Chen, Jing</creator><general>Science Press</general><general>Springer Nature B.V</general><general>State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences,China Meteorological Administration, Beijing 100081, China%National Meteorological Center, China Meteorological Administration, Beijing 100081, China</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7TG</scope><scope>F1W</scope><scope>H96</scope><scope>KL.</scope><scope>L.G</scope><scope>2B.</scope><scope>4A8</scope><scope>92I</scope><scope>93N</scope><scope>PSX</scope><scope>TCJ</scope></search><sort><creationdate>20190901</creationdate><title>Recent Progress in Numerical Atmospheric Modeling in China</title><author>Yu, Rucong ; Zhang, Yi ; Wang, Jianjie ; Li, Jian ; Chen, Haoming ; Gong, Jiandong ; Chen, Jing</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c350t-2600d36656a55f26d64a21e9811397ebad0b3ce9a74a5cbc5c6c5b06b8d4101a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Atmospheric models</topic><topic>Atmospheric Sciences</topic><topic>Computer simulation</topic><topic>Computers</topic><topic>Data assimilation</topic><topic>Data collection</topic><topic>Earth and Environmental Science</topic><topic>Earth Sciences</topic><topic>Ensemble forecasting</topic><topic>Evaluation</topic><topic>Forecasting</topic><topic>Formulations</topic><topic>Geophysics/Geodesy</topic><topic>Mathematical models</topic><topic>Meteorology</topic><topic>Modelling</topic><topic>National Reports to the IUGG by Chinese National Committee for IAMAS</topic><topic>Parallel computers</topic><topic>Parameterization</topic><topic>Performance measurement</topic><topic>Physics</topic><topic>Review</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Yu, Rucong</creatorcontrib><creatorcontrib>Zhang, Yi</creatorcontrib><creatorcontrib>Wang, Jianjie</creatorcontrib><creatorcontrib>Li, Jian</creatorcontrib><creatorcontrib>Chen, Haoming</creatorcontrib><creatorcontrib>Gong, Jiandong</creatorcontrib><creatorcontrib>Chen, Jing</creatorcontrib><collection>CrossRef</collection><collection>Meteorological & Geoastrophysical 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><collection>Wanfang Data Journals - Hong Kong</collection><collection>WANFANG Data Centre</collection><collection>Wanfang Data Journals</collection><collection>万方数据期刊 - 香港版</collection><collection>China Online Journals (COJ)</collection><collection>China Online Journals (COJ)</collection><jtitle>Advances in atmospheric sciences</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Yu, Rucong</au><au>Zhang, Yi</au><au>Wang, Jianjie</au><au>Li, Jian</au><au>Chen, Haoming</au><au>Gong, Jiandong</au><au>Chen, Jing</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Recent Progress in Numerical Atmospheric Modeling in China</atitle><jtitle>Advances in atmospheric sciences</jtitle><stitle>Adv. Atmos. Sci</stitle><date>2019-09-01</date><risdate>2019</risdate><volume>36</volume><issue>9</issue><spage>938</spage><epage>960</epage><pages>938-960</pages><issn>0256-1530</issn><eissn>1861-9533</eissn><abstract>This review summarizes the scientific and technical progress in atmospheric modeling in China since 2011, including the dynamical core, model physics, data assimilation, ensemble forecasting, and model evaluation strategies. In terms of the dynamical core, important efforts have been made in the improvement of the existing model formulations and in exploring new modeling approaches that can better adapt to massively parallel computers and global multiscale modeling. With regard to model physics, various achievements in physical representations have been made, especially a trend toward scale-aware parameterization for accommodating the increase of model resolution. In the field of data assimilation, a 4D-Var system has been developed and is operationally used by the National Meteorological Center of China, and its performance is promising. Furthermore, ensemble forecasting has played a more important role in operational forecast systems and progressed in many fundamental techniques. Model evaluation strategies, including key performance metrics and standardized experimental protocols, have been proposed and widely applied to better understand the strengths and weaknesses of the systems, offering key routes for model improvement. The paper concludes with a concise summary of the status quo and a brief outlook in terms of future development.</abstract><cop>Heidelberg</cop><pub>Science Press</pub><doi>10.1007/s00376-019-8203-1</doi><tpages>23</tpages></addata></record> |
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subjects | Atmospheric models Atmospheric Sciences Computer simulation Computers Data assimilation Data collection Earth and Environmental Science Earth Sciences Ensemble forecasting Evaluation Forecasting Formulations Geophysics/Geodesy Mathematical models Meteorology Modelling National Reports to the IUGG by Chinese National Committee for IAMAS Parallel computers Parameterization Performance measurement Physics Review |
title | Recent Progress in Numerical Atmospheric Modeling in China |
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