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第1行： − 此词条暂由彩云小译翻译，翻译字数共2959，未经人工整理和审校，带来阅读不便，请见谅。+ − + + + 第103行：
第105行： − + − + − == Applications 应用 ==+ − − {{Main|Climate model|General circulation model}} − − In 1956, Norman Phillips developed a mathematical model that realistically depicted monthly and seasonal patterns in the troposphere. This was the first successful [[climate model]].<ref name="Phillips">{{cite journal | url=http://www.phy.pku.edu.cn/climate/class/cm2010/Phillips_QJRMS_1956.pdf | title=The general circulation of the atmosphere: a numerical experiment | journal=[[Quarterly Journal of the Royal Meteorological Society]] | author=Norman A. Phillips | date=April 1956 | volume=82 | issue=352 | pages=123–154 | doi=10.1002/qj.49708235202 | bibcode=1956QJRMS..82..123P}}</ref><ref name="Cox210">{{cite book | title=Storm Watchers | author=John D. Cox | publisher=John Wiley & Sons, Inc. | page=[https://archive.org/details/stormwatcherstur00cox_df1/page/210 210] | year=2002 | isbn=978-0-471-38108-2 | url=https://archive.org/details/stormwatcherstur00cox_df1/page/210 }}</ref> Several groups then began working to create [[general circulation model]]s.<ref name="Lynch Ch10"/> The first general circulation climate model combined oceanic and atmospheric processes and was developed in the late 1960s at the [[Geophysical Fluid Dynamics Laboratory]], a component of the U.S. [[National Oceanic and Atmospheric Administration]].<ref>{{cite web | url=http://celebrating200years.noaa.gov/breakthroughs/climate_model/welcome.html | title=The First Climate Model | author=National Oceanic and Atmospheric Administration | author-link=National Oceanic and Atmospheric Administration | date=22 May 2008 | access-date=8 January 2011}}</ref> By the early 1980s, the U.S. [[National Center for Atmospheric Research]] had developed the Community Atmosphere Model (CAM), which can be run by itself or as the atmospheric component of the [[Community Climate System Model]]. The latest update (version 3.1) of the standalone CAM was issued on 1 February 2006.<ref>{{Cite web|url=http://www.cesm.ucar.edu/models/atm-cam/download/|title=CAM 3.1 Download|website=www.cesm.ucar.edu|access-date=2019-06-25}}</ref><ref>{{cite web | url=http://www.cesm.ucar.edu/models/atm-cam/docs/description/description.pdf | title=Description of the NCAR Community Atmosphere Model (CAM 3.0) | author=William D. Collins | publisher=[[University Corporation for Atmospheric Research]] | date=June 2004 | access-date=3 January 2011 | display-authors=et al.}}</ref><ref>{{cite web | url=http://www.cesm.ucar.edu/models/atm-cam/ | title=CAM3.0 COMMUNITY ATMOSPHERE MODEL | publisher=[[University Corporation for Atmospheric Research]] | access-date=6 February 2018}}</ref> In 1986, efforts began to initialize and model soil and vegetation types, resulting in more realistic forecasts.<ref>{{cite journal | url=http://www.geog.ucla.edu/~yxue/pdf/1996jgr.pdf | title=Impact of vegetation properties on U. S. summer weather prediction | journal=[[Journal of Geophysical Research]] | author1=Yongkang Xue | author2=Michael J. Fennessey | name-list-style=amp | date=20 March 1996 | volume=101 | issue=D3 | page=7419 | access-date=6 January 2011 | bibcode=1996JGR...101.7419X | doi=10.1029/95JD02169 | url-status=dead | archive-url=https://web.archive.org/web/20100710080304/http://www.geog.ucla.edu/~yxue/pdf/1996jgr.pdf | archive-date=10 July 2010| citeseerx=10.1.1.453.551 }}</ref> Coupled ocean-atmosphere climate models, such as the [[Hadley Centre for Climate Prediction and Research]]'s [[HadCM3]] model, are being used as inputs for [[climate change]] studies.<ref name="Lynch Ch10">{{cite book | chapter-url=https://books.google.com/books?id=EV5bZqOO7kkC&pg=PA208 | title=The Emergence of Numerical Weather Prediction: Richardson's Dream | chapter=The ENIAC Integrations | author=Peter Lynch | publisher=[[Cambridge University Press]] | year=2006 | isbn=978-0-521-85729-1 | page=208 | access-date=6 February 2018}}</ref> − − In 1956, Norman Phillips developed a mathematical model that realistically depicted monthly and seasonal patterns in the troposphere. This was the first successful climate model. Several groups then began working to create general circulation models. The first general circulation climate model combined oceanic and atmospheric processes and was developed in the late 1960s at the Geophysical Fluid Dynamics Laboratory, a component of the U.S. National Oceanic and Atmospheric Administration. By the early 1980s, the U.S. National Center for Atmospheric Research had developed the Community Atmosphere Model (CAM), which can be run by itself or as the atmospheric component of the Community Climate System Model. The latest update (version 3.1) of the standalone CAM was issued on 1 February 2006. In 1986, efforts began to initialize and model soil and vegetation types, resulting in more realistic forecasts. Coupled ocean-atmosphere climate models, such as the Hadley Centre for Climate Prediction and Research's HadCM3 model, are being used as inputs for climate change studies. − − 1956年，诺曼 · 菲利普斯开发了一个数学模型，这个模型真实地描述了对流层的每月和季节的模式。这是第一个成功的气候模型。几个小组随后开始建立大体循环模型。第一个大气环流气候模式结合了海洋和大气过程，于20世纪60年代末在美国地球物理流体动力学实验室气候研究中心发展起来，该中心是美国美国国家海洋和大气管理局气候研究中心的一个组成部分。到20世纪80年代早期，美国国家大气研究中心开发了社区大气模型(CAM) ，它可以自己运行，也可以作为社区气候系统模型的大气成分。最新更新(3.1版本)已于2006年2月1日发出。在1986年，开始努力初始化和模型的土壤和植被类型，导致更现实的预测。耦合的海洋-大气气候模型，如哈德利气候预测与研究中心的 hadcm3模型，正被用作气候变化研究的输入。 − − 【终稿】1956年，诺曼·菲利普斯（Norman Phillips）开发了一个真实描述对流层逐月和逐季节模式的数学模型。这是第一个成功的气候模式。几个小组随后开始开创大气循环模式。20世纪60年代，第一个耦合海洋和大气过程的循环气候模式在美国地球物理流体动力学实验室气候研究中心被开发出来，该中心是美国美国国家海洋和大气管理局气候研究中心的一个分部门。到20世纪80年代早期，美国国家大气研究中心开发了社区大气模式(CAM) ，既可以单独运行，也可以作为社区气候系统模型的大气模块部分运行。最新的独立CAM(3.1版本)已于2006年2月1日发布。在1986年，人们开始投入初始化和模拟的土壤、植被类型，以实现更真实的预测。耦合的海洋-大气气候模式，如哈德利气候预测与研究中心的 HadCM3模式（the Hadley Centre for Climate Prediction and Research's HadCM3 model），正被用作气候变化研究的输入。 − − ===Limited area modeling 有限区域模拟=== − [[File:Ernesto2006modelspread.png|thumb|right|Model spread with [[Hurricane Ernesto (2006)]] within the National Hurricane Center limited area models|链接=Special:FilePath/Ernesto2006modelspread.png]] − [[Air pollution forecasting|Air pollution forecasts]] depend on atmospheric models to provide [[fluid flow]] information for tracking the movement of pollutants.<ref>{{cite journal | author1=Alexander Baklanov | author2=Alix Rasmussen | author3=Barbara Fay | author4=Erik Berge | author5=Sandro Finardi | title=Potential and Shortcomings of Numerical Weather Prediction Models in Providing Meteorological Data for Urban Air Pollution Forecasting | journal=Water, Air, & Soil Pollution: Focus | date=September 2002 | volume=2 | issue=5 | pages=43–60 | doi=10.1023/A:1021394126149| s2cid=94747027 }}</ref> In 1970, a private company in the U.S. developed the regional Urban Airshed Model (UAM), which was used to forecast the effects of air pollution and [[acid rain]]. In the mid- to late-1970s, the [[United States Environmental Protection Agency]] took over the development of the UAM and then used the results from a regional air pollution study to improve it. Although the UAM was developed for [[California]], it was during the 1980s used elsewhere in North America, Europe, and Asia.<ref name="Steyn, D. G. 1991 241–242"/> − Air pollution forecasts depend on atmospheric models to provide fluid flow information for tracking the movement of pollutants. In 1970, a private company in the U.S. developed the regional Urban Airshed Model (UAM), which was used to forecast the effects of air pollution and acid rain. In the mid- to late-1970s, the United States Environmental Protection Agency took over the development of the UAM and then used the results from a regional air pollution study to improve it. Although the UAM was developed for California, it was during the 1980s used elsewhere in North America, Europe, and Asia.+ + − 空气污染预报依靠大气模型来提供流体流动信息，以跟踪污染物的运动。1970年，美国的一家私营公司开发了区域城市气流模型(UAM) ，用于预测空气污染和酸雨的影响。在1970年代中后期，美国环境保护局接管了 UAM 的开发工作，然后利用区域空气污染研究的结果来改进 UAM。虽然 UAM 是为加利福尼亚州开发的，但在20世纪80年代，它在北美、欧洲和亚洲的其他地方得到了应用。+ − 【终稿】空气污染预报依靠大气模式来提供流体流动信息，从而跟踪污染物运动。1970年，美国的一家私营公司开发了区域城市气流模式（the regional Urban Airshed Model，UAM），用于预报空气污染及酸雨的影响。在20世纪70年代年代中后期，美国环境保护局接管了UAM的开发工作，并利用区域空气污染研究的结果对其改进。尽管UAM是为加利福利亚州开发的，但到了20世纪80年代，它在北美、欧洲和亚洲的部分地区投入应用。 − The Movable Fine-Mesh model, which began operating in 1978, was the first [[tropical cyclone forecast model]] to be based on [[Atmospheric dynamics#Dynamic meteorology|atmospheric dynamics]].<ref name="Shuman W&F"/> Despite the constantly improving dynamical model guidance made possible by increasing computational power, it was not until the 1980s that numerical weather prediction (NWP) showed [[Forecast skill|skill]] in forecasting the track of tropical cyclones. And it was not until the 1990s that NWP consistently outperformed [[statistical model|statistical]] or simple dynamical models.<ref>{{cite web | url=http://www.nhc.noaa.gov/verification/verify6.shtml | publisher=[[National Hurricane Center]] | date=20 April 2010 | access-date=2 January 2011 | author=James Franklin | title=National Hurricane Center Forecast Verification | author-link=James Franklin (meteorologist) | archive-url=https://web.archive.org/web/20110102062753/http://www.nhc.noaa.gov/verification/verify6.shtml | archive-date=2 January 2011 | url-status=live}}</ref> Predicting the intensity of tropical cyclones using NWP has also been challenging. As of 2009, dynamical guidance remained less skillful than statistical methods.<ref>{{cite journal | author1=Edward N. Rappaport | author2=James L. Franklin | author3=Lixion A. Avila | author4=Stephen R. Baig | author5=John L. Beven II | author6=Eric S. Blake | author7=Christopher A. Burr | author8=Jiann-Gwo Jiing | author9=Christopher A. Juckins | author10=Richard D. Knabb | author11=Christopher W. Landsea | author12=Michelle Mainelli | author13=Max Mayfield | author14=Colin J. McAdie | author15=Richard J. Pasch | author16=Christopher Sisko | author17=Stacy R. Stewart | author18=Ahsha N. Tribble | title=Advances and Challenges at the National Hurricane Center | journal=[[Weather and Forecasting]] | date=April 2009 | volume=24 | issue=2 | pages=395–419 | doi=10.1175/2008WAF2222128.1 | bibcode=2009WtFor..24..395R| citeseerx=10.1.1.207.4667 }}</ref>+ − The Movable Fine-Mesh model, which began operating in 1978, was the first tropical cyclone forecast model to be based on atmospheric dynamics. Despite the constantly improving dynamical model guidance made possible by increasing computational power, it was not until the 1980s that numerical weather prediction (NWP) showed skill in forecasting the track of tropical cyclones. And it was not until the 1990s that NWP consistently outperformed statistical or simple dynamical models. Predicting the intensity of tropical cyclones using NWP has also been challenging. As of 2009, dynamical guidance remained less skillful than statistical methods. − 可移动细网模型于1978年开始运行，是第一个基于大气动力学的热带气旋预报模型模型。尽管由于计算能力的提高，不断改进的动力学模型指南成为可能，但直到20世纪80年代，数值天气预报才显示出预报热带气旋路径的技术。直到20世纪90年代，数值天气预报才始终优于统计或简单的动力学模型。使用数值预报方法预报热带气旋的强度也是一个挑战。截至2009年，动态指导仍然不如统计方法熟练。+ + + + + + − 【终稿】可移动细网格模式（the Movable Fine-Mesh model）在1978年开始运行，是第一个基于大气动力学的热带气旋预报模式。尽管由于不断增强的计算机算力，持续改进的动力学模式指导成为可能，但是直到20世纪80年代，数值天气预报才显示出预报热带气旋路径的能力；直到20世纪90年代才持续地好于统计模型或简单的动力学模型。使用数值预报方法预测热带气旋强调也始终难度较高。直到2009年，动力学控制的方法仍不如统计方法效果好。 − + − * [[Atmospheric reanalysis]] − * [[Climate model]] − * [[Numerical weather prediction]] − * [[Upper-atmospheric models]] − * [[Static atmospheric model]] − − * Atmospheric reanalysis − * Climate model − * Numerical weather prediction − * Upper-atmospheric models − * Static atmospheric model − − − 【终稿】 − − * 大气再分析 − * 气候模式 − * 数值天气预报 − * 高层大气模式 − * 稳定大气模式 − − = = = = = − * 大气重新分析 − * 气候模式 − * 数值天气预报 − * 高层大气模式 − * 静态大气模式 − − == References == − + − * − ==External links== − * [https://web.archive.org/web/20110921153007/http://www.mmm.ucar.edu/wrf/users/download/get_source2.html WRF Source Codes and Graphics Software Download Page] − * [https://web.archive.org/web/20140712133145/http://bridge.atmet.org/users/software.php RAMS source code available under the GNU General Public License] − * [https://web.archive.org/web/20110928000959/http://www.mmm.ucar.edu/mm5/mm5v3/wherev3.html MM5 Source Code download] − * [http://www.caps.ou.edu/ARPS The source code of ARPS] − * [http://www.ventusky.com/ Model Visualisation] − * WRF Source Codes and Graphics Software Download Page+ − * RAMS source code available under the GNU General Public License − * MM5 Source Code download − * The source code of ARPS − * Model Visualisation − − 第194行：
第143行： + + + + + + − Categories: Numerical climate and weather models − 【终稿】数值气候与天气模式+ + − {{Atmospheric, Oceanographic and Climate Models|state=expanded}} − {{Computer modeling}} − {{DEFAULTSORT:Atmospheric Model}} − [[Category:Numerical climate and weather models]] − [[Category:Articles containing video clips]] + + − Category:Numerical climate and weather models − Category:Articles containing video clips − 类别: 数值气候和天气模型类别: 包含视频剪辑的文章 − <noinclude>+ − <small>This page was moved from [[wikipedia:en:Atmospheric model]]. Its edit history can be viewed at [[大气模式/edithistory]]</small></noinclude> − +
无编辑摘要
{{#seo:
|keywords=大气模式,数学模型,数值预报
|description=是围绕控制大气运动的一整套原始的动力学方程所建立的数学模型
}}
[[File:GFS 850 MB.PNG|right|250px|thumb|一次850mbar处地势高度和温度的96小时预报]]
[[File:GFS 850 MB.PNG|right|250px|thumb|一次850mbar处地势高度和温度的96小时预报]]
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== Applications ==
==应用 ==
===气候模拟===
1956年，诺曼·菲利普斯 Norman Phillips开发了一个真实描述对流层逐月和逐季节模式的数学模型。这是第一个成功的气候模式。<ref name="Phillips">{{cite journal | url=http://www.phy.pku.edu.cn/climate/class/cm2010/Phillips_QJRMS_1956.pdf | title=The general circulation of the atmosphere: a numerical experiment | journal=[[Quarterly Journal of the Royal Meteorological Society]] | author=Norman A. Phillips | date=April 1956 | volume=82 | issue=352 | pages=123–154 | doi=10.1002/qj.49708235202 | bibcode=1956QJRMS..82..123P}}</ref><ref name="Cox210">{{cite book | title=Storm Watchers | author=John D. Cox | publisher=John Wiley & Sons, Inc. | page=[https://archive.org/details/stormwatcherstur00cox_df1/page/210 210] | year=2002 | isbn=978-0-471-38108-2 | url=https://archive.org/details/stormwatcherstur00cox_df1/page/210 }}</ref>几个小组随后开始开创大气循环模式。<ref name="Lynch Ch10"/>20世纪60年代，第一个耦合海洋和大气过程的循环气候模式在美国地球物理流体动力学实验室气候研究中心被开发出来，该中心是美国美国国家海洋和大气管理局气候研究中心的一个分部门。<ref>{{cite web | url=http://celebrating200years.noaa.gov/breakthroughs/climate_model/welcome.html | title=The First Climate Model | author=National Oceanic and Atmospheric Administration | author-link=National Oceanic and Atmospheric Administration | date=22 May 2008 | access-date=8 January 2011}}</ref>到20世纪80年代早期，美国国家大气研究中心开发了社区大气模式(CAM) ，既可以单独运行，也可以作为社区气候系统模型的大气模块部分运行。最新的独立CAM(3.1版本)已于2006年2月1日发布。<ref>{{Cite web|url=http://www.cesm.ucar.edu/models/atm-cam/download/|title=CAM 3.1 Download|website=www.cesm.ucar.edu|access-date=2019-06-25}}</ref><ref>{{cite web | url=http://www.cesm.ucar.edu/models/atm-cam/docs/description/description.pdf | title=Description of the NCAR Community Atmosphere Model (CAM 3.0) | author=William D. Collins | publisher=[[University Corporation for Atmospheric Research]] | date=June 2004 | access-date=3 January 2011 | display-authors=et al.}}</ref><ref>{{cite web | url=http://www.cesm.ucar.edu/models/atm-cam/ | title=CAM3.0 COMMUNITY ATMOSPHERE MODEL | publisher=[[University Corporation for Atmospheric Research]] | access-date=6 February 2018}}</ref>在1986年，人们开始投入初始化和模拟的土壤、植被类型，以实现更真实的预测。<ref>{{cite journal | url=http://www.geog.ucla.edu/~yxue/pdf/1996jgr.pdf | title=Impact of vegetation properties on U. S. summer weather prediction | journal=[[Journal of Geophysical Research]] | author1=Yongkang Xue | author2=Michael J. Fennessey | name-list-style=amp | date=20 March 1996 | volume=101 | issue=D3 | page=7419 | access-date=6 January 2011 | bibcode=1996JGR...101.7419X | doi=10.1029/95JD02169 | url-status=dead | archive-url=https://web.archive.org/web/20100710080304/http://www.geog.ucla.edu/~yxue/pdf/1996jgr.pdf | archive-date=10 July 2010| citeseerx=10.1.1.453.551 }}</ref>耦合的海洋-大气气候模式，如哈德利气候预测与研究中心的 HadCM3模式，正被用作气候变化研究的输入。<ref name="Lynch Ch10">{{cite book | chapter-url=https://books.google.com/books?id=EV5bZqOO7kkC&pg=PA208 | title=The Emergence of Numerical Weather Prediction: Richardson's Dream | chapter=The ENIAC Integrations | author=Peter Lynch | publisher=[[Cambridge University Press]] | year=2006 | isbn=978-0-521-85729-1 | page=208 | access-date=6 February 2018}}</ref>
===Climate modeling 气候模拟===
===有限区域模拟===
[[File:Ernesto2006modelspread.png|thumb|right|Model spread with [[Hurricane Ernesto (2006)]] within the National Hurricane Center limited area models]]
'''空气污染预报 Air pollution forecasting'''依靠大气模式来提供流体流动信息，从而跟踪污染物运动。<ref>{{cite journal | author1=Alexander Baklanov | author2=Alix Rasmussen | author3=Barbara Fay | author4=Erik Berge | author5=Sandro Finardi | title=Potential and Shortcomings of Numerical Weather Prediction Models in Providing Meteorological Data for Urban Air Pollution Forecasting | journal=Water, Air, & Soil Pollution: Focus | date=September 2002 | volume=2 | issue=5 | pages=43–60 | doi=10.1023/A:1021394126149| s2cid=94747027 }}</ref>1970年，美国的一家私营公司开发了区域城市气流模式（the regional Urban Airshed Model，UAM），用于预报空气污染及酸雨的影响。在20世纪70年代年代中后期，美国环境保护局接管了UAM的开发工作，并利用区域空气污染研究的结果对其改进。尽管UAM是为加利福利亚州开发的，但到了20世纪80年代，它在北美、欧洲和亚洲的部分地区投入应用。<ref name="Steyn, D. G. 1991 241–242"/>
'''可移动细网格模式 the Movable Fine-Mesh model'''在1978年开始运行，是第一个基于大气动力学的热带气旋预报模式。<ref name="Shuman W&F"/>尽管由于不断增强的计算机算力，持续改进的动力学模式指导成为可能，但是直到20世纪80年代，数值天气预报才显示出预报热带气旋路径的能力；直到20世纪90年代才持续地好于统计模型或简单的动力学模型。<ref>{{cite web | url=http://www.nhc.noaa.gov/verification/verify6.shtml | publisher=[[National Hurricane Center]] | date=20 April 2010 | access-date=2 January 2011 | author=James Franklin | title=National Hurricane Center Forecast Verification | author-link=James Franklin (meteorologist) | archive-url=https://web.archive.org/web/20110102062753/http://www.nhc.noaa.gov/verification/verify6.shtml | archive-date=2 January 2011 | url-status=live}}</ref>使用数值预报方法预测热带气旋强调也始终难度较高。直到2009年，动力学控制的方法仍不如统计方法效果好。<ref>{{cite journal | author1=Edward N. Rappaport | author2=James L. Franklin | author3=Lixion A. Avila | author4=Stephen R. Baig | author5=John L. Beven II | author6=Eric S. Blake | author7=Christopher A. Burr | author8=Jiann-Gwo Jiing | author9=Christopher A. Juckins | author10=Richard D. Knabb | author11=Christopher W. Landsea | author12=Michelle Mainelli | author13=Max Mayfield | author14=Colin J. McAdie | author15=Richard J. Pasch | author16=Christopher Sisko | author17=Stacy R. Stewart | author18=Ahsha N. Tribble | title=Advances and Challenges at the National Hurricane Center | journal=[[Weather and Forecasting]] | date=April 2009 | volume=24 | issue=2 | pages=395–419 | doi=10.1175/2008WAF2222128.1 | bibcode=2009WtFor..24..395R| citeseerx=10.1.1.207.4667 }}</ref>
==另见==
* [[大气再分析]]
* [[气候模式]]
* [[数值天气预报]]
* [[高层大气模式]]
* [[稳定大气模式]]
==See also 另见==
== 参考文献 ==
{{Reflist|2}}
{{Reflist|2}}
==Further reading 进一步阅读==
==进一步阅读==
{{Refbegin}}
{{Refbegin}}
*{{cite book |author1=Roulstone, Ian |author2=Norbury, John |title=Invisible in the Storm: the role of mathematics in understanding weather |location=Princeton |publisher=Princeton University Press |year=2013 |isbn=978-0-691-15272-1 }}
*{{cite book |author1=Roulstone, Ian |author2=Norbury, John |title=Invisible in the Storm: the role of mathematics in understanding weather |location=Princeton |publisher=Princeton University Press |year=2013 |isbn=978-0-691-15272-1 }}
{{Refend}}
{{Refend}}
== 外部链接 ==
= 外部链接 =
*[https://web.archive.org/web/20110921153007/http://www.mmm.ucar.edu/wrf/users/download/get_source2.html WRF 源码和绘图软件下载页]
*[https://web.archive.org/web/20110921153007/http://www.mmm.ucar.edu/wrf/users/download/get_source2.html WRF 源码和绘图软件下载页]
*[https://web.archive.org/web/20140712133145/http://bridge.atmet.org/users/software.php RAMS 源码（ GNU通用公共许可协议下可用）]
*[https://web.archive.org/web/20140712133145/http://bridge.atmet.org/users/software.php RAMS 源码（ GNU通用公共许可协议下可用）]
*[http://www.ventusky.com/ 模型可视化]
*[http://www.ventusky.com/ 模型可视化]
== 编者推荐 ==
===书籍===
[[File:《数值天气与气候预测》.jpg|300px|《数值天气和气候预测》封面]]
====《数值天气和气候预测》（托马斯·汤姆金斯·沃纳著）====
本教科书为研究生、研究人员和专业人士提供了关于天气和气候预测综合而易懂的论述。针对大气模式的使用，讲授其优点、缺陷和佳实践，对在各个方面应用模式的学者们来说是本理想的书籍。书中描述了不同的数值方法、资料同化、集合方法、可预报性、陆面模拟、气候模拟和降尺度、计算流体动力模式、基于模式研究的试验设计、检验方法、业务预报，以及空气质量模式和洪水预报等专业应用。本书基于作者在宾夕法尼亚州立大学和科罗拉多大学30多年所教授的课程，也得益于作者在美国国家大气研究中心（NCAR）的模式实践经历。 本书将满足在研究和业务应用中需要了解大气模式的人士，适合作为天气和气候预测分支学科的教科书，也可作为具有大气科学、气象学、气候学、环境科学、地理学及地球物理流体力学／动力学等研究背景的专业人士作为参考用书。
====《WRF-CMAQ气象化学耦合模式的运用及分析》（赵锦慧著）====
黑碳气溶胶是大气污染物的重要组成部分，参与大气物理、大气化学、大气光化学过程，对气候、环境及人体健康等方面产生影响。《WRF-CMAQ气象化学耦合模式的运用过程分析》基于WRF-CMAQ模型的运算结果，分析黑碳气溶胶的分布规律。首先介绍CMAQ模型、WRF模型，确定排放源清单的概况，然后介绍基于WRF-CMAQ气象化学耦合模型的参数设置，运行此模型得到武汉地区黑碳气溶胶的质量浓度，最后以武汉市一年期的黑碳气溶胶实测数据作为实例进行验证，确定耦合模型的精度。
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