• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

美国国家航空航天局地球观测系统成分预测建模系统GEOS-CF v1.0:平流层成分

NASA GEOS Composition Forecast Modeling System GEOS-CF v1.0: Stratospheric Composition.

作者信息

Knowland K E, Keller C A, Wales P A, Wargan K, Coy L, Johnson M S, Liu J, Lucchesi R A, Eastham S D, Fleming E, Liang Q, Leblanc T, Livesey N J, Walker K A, Ott L E, Pawson S

机构信息

Universities Space Research Association (USRA)/GESTAR Columbia MD USA.

NASA Goddard Space Flight Center (GSFC) Global Modeling and Assimilation Office (GMAO) Greenbelt MD USA.

出版信息

J Adv Model Earth Syst. 2022 Jun;14(6):e2021MS002852. doi: 10.1029/2021MS002852. Epub 2022 Jun 7.

DOI:10.1029/2021MS002852
PMID:35864944
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9287101/
Abstract

The NASA Goddard Earth Observing System (GEOS) Composition Forecast (GEOS-CF) provides recent estimates and 5-day forecasts of atmospheric composition to the public in near-real time. To do this, the GEOS Earth system model is coupled with the GEOS-Chem tropospheric-stratospheric unified chemistry extension (UCX) to represent composition from the surface to the top of the GEOS atmosphere (0.01 hPa). The GEOS-CF system is described, including updates made to the GEOS-Chem UCX mechanism within GEOS-CF for improved representation of stratospheric chemistry. Comparisons are made against balloon, lidar, and satellite observations for stratospheric composition, including measurements of ozone (O) and important nitrogen and chlorine species related to stratospheric O recovery. The GEOS-CF nudges the stratospheric O toward the GEOS Forward Processing (GEOS FP) assimilated O product; as a result the stratospheric O in the GEOS-CF historical estimate agrees well with observations. During abnormal dynamical and chemical environments such as the 2020 polar vortexes, the GEOS-CF O forecasts are more realistic than GEOS FP O forecasts because of the inclusion of the complex GEOS-Chem UCX stratospheric chemistry. Overall, the spatial patterns of the GEOS-CF simulated concentrations of stratospheric composition agree well with satellite observations. However, there are notable biases-such as low NO and HNO in the polar regions and generally low HCl throughout the stratosphere-and future improvements to the chemistry mechanism and emissions are discussed. GEOS-CF is a new tool for the research community and instrument teams observing trace gases in the stratosphere and troposphere, providing near-real-time three-dimensional gridded information on atmospheric composition.

摘要

美国国家航空航天局戈达德地球观测系统(GEOS)成分预报(GEOS-CF)近乎实时地向公众提供大气成分的近期估算值和5天预报。为此,GEOS地球系统模型与GEOS-化学对流层-平流层统一化学扩展(UCX)相耦合,以呈现从地表到GEOS大气层顶部(0.01百帕)的成分。描述了GEOS-CF系统,包括对GEOS-CF中GEOS-化学UCX机制所做的更新,以改进对平流层化学的呈现。针对平流层成分,与气球、激光雷达和卫星观测数据进行了比较,包括臭氧(O)以及与平流层O恢复相关的重要氮和氯物种的测量。GEOS-CF将平流层O向GEOS前向处理(GEOS FP)同化的O产品进行调整;因此,GEOS-CF历史估算中的平流层O与观测结果吻合良好。在异常的动力和化学环境(如2020年的极地涡旋)中,由于纳入了复杂的GEOS-化学UCX平流层化学,GEOS-CF的O预报比GEOS FP的O预报更符合实际情况。总体而言,GEOS-CF模拟的平流层成分浓度的空间模式与卫星观测结果吻合良好。然而,存在明显偏差,如极地地区的NO和HNO较低,以及整个平流层的HCl普遍较低,并讨论了未来对化学机制和排放的改进。GEOS-CF是研究界和观测平流层和对流层微量气体的仪器团队的一种新工具,提供关于大气成分的近乎实时的三维网格化信息。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a541/9287101/c77c77e3eafe/JAME-14-0-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a541/9287101/1db7ee0c80a5/JAME-14-0-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a541/9287101/44b91a533b97/JAME-14-0-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a541/9287101/178adda6784b/JAME-14-0-g016.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a541/9287101/82a0b7eed1c9/JAME-14-0-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a541/9287101/dc819359266c/JAME-14-0-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a541/9287101/f57a5dbf8c14/JAME-14-0-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a541/9287101/3cff285ea391/JAME-14-0-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a541/9287101/9147819a6768/JAME-14-0-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a541/9287101/d409b9be2bee/JAME-14-0-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a541/9287101/89feabe81caf/JAME-14-0-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a541/9287101/b874c3dad969/JAME-14-0-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a541/9287101/53a07aa546e9/JAME-14-0-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a541/9287101/95670605ee6b/JAME-14-0-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a541/9287101/68fbfc9e9c17/JAME-14-0-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a541/9287101/f14de4d256bc/JAME-14-0-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a541/9287101/c77c77e3eafe/JAME-14-0-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a541/9287101/1db7ee0c80a5/JAME-14-0-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a541/9287101/44b91a533b97/JAME-14-0-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a541/9287101/178adda6784b/JAME-14-0-g016.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a541/9287101/82a0b7eed1c9/JAME-14-0-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a541/9287101/dc819359266c/JAME-14-0-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a541/9287101/f57a5dbf8c14/JAME-14-0-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a541/9287101/3cff285ea391/JAME-14-0-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a541/9287101/9147819a6768/JAME-14-0-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a541/9287101/d409b9be2bee/JAME-14-0-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a541/9287101/89feabe81caf/JAME-14-0-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a541/9287101/b874c3dad969/JAME-14-0-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a541/9287101/53a07aa546e9/JAME-14-0-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a541/9287101/95670605ee6b/JAME-14-0-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a541/9287101/68fbfc9e9c17/JAME-14-0-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a541/9287101/f14de4d256bc/JAME-14-0-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a541/9287101/c77c77e3eafe/JAME-14-0-g015.jpg

相似文献

1
NASA GEOS Composition Forecast Modeling System GEOS-CF v1.0: Stratospheric Composition.美国国家航空航天局地球观测系统成分预测建模系统GEOS-CF v1.0:平流层成分
J Adv Model Earth Syst. 2022 Jun;14(6):e2021MS002852. doi: 10.1029/2021MS002852. Epub 2022 Jun 7.
2
Description of the NASA GEOS Composition Forecast Modeling System GEOS-CF v1.0.美国国家航空航天局地球观测系统成分预测建模系统GEOS-CF v1.0的描述。
J Adv Model Earth Syst. 2021 Apr;13(4):e2020MS002413. doi: 10.1029/2020MS002413. Epub 2021 Apr 7.
3
Assessment of upper tropospheric and stratospheric water vapor and ozone in reanalyses as part of S-RIP.作为平流层-对流层相互作用研究计划(S-RIP)一部分,对再分析资料中对流层上部和平流层水汽及臭氧的评估。
Atmos Chem Phys. 2017 Oct;17(20):12743-12778. doi: 10.5194/acp-17-12743-2017. Epub 2017 Oct 26.
4
Evaluation of NASA's high-resolution global composition simulations: Understanding a pollution event in the Chesapeake Bay during the summer 2017 OWLETS campaign.美国国家航空航天局高分辨率全球成分模拟评估:了解2017年夏季切萨皮克湾OWLETS活动期间的一次污染事件。
Atmos Environ (1994). 2020 Feb 1;222. doi: 10.1016/j.atmosenv.2019.117133. Epub 2019 Nov 16.
5
Stratospheric intrusion-influenced ozone air quality exceedances investigated in the NASA MERRA-2 Reanalysis.利用美国国家航空航天局(NASA)的现代-era回顾性分析研究与应用-2(MERRA-2)再分析数据,对平流层侵入影响下的臭氧空气质量超标情况进行了调查。
Geophys Res Lett. 2017 Sep 7;44(20):10691-10701. doi: 10.1002/2017gl074532. Epub 2017 Oct 28.
6
Chemical Mechanisms and Their Applications in the Goddard Earth Observing System (GEOS) Earth System Model.化学机制及其在戈达德地球观测系统(GEOS)地球系统模型中的应用
J Adv Model Earth Syst. 2017 Dec;9(8):3019-3044. doi: 10.1002/2017MS001011. Epub 2017 Dec 26.
7
Impacts of Interactive Stratospheric Chemistry on Antarctic and Southern Ocean Climate Change in the Goddard Earth Observing System - Version 5 (GEOS-5).交互式平流层化学对戈达德地球观测系统第5版(GEOS - 5)中南极和南大洋气候变化的影响。
J Clim. 2016;29(9):3199-3218. doi: 10.1175/JCLI-D-15-0572.1. Epub 2016 Apr 19.
8
Evaluation of WRF-Chem air quality forecasts during the AEROMMA and STAQS 2023 field campaigns.评估 WRF-Chem 空气质量预报在 AEROMMA 和 STAQS 2023 实地考察期间的表现。
J Air Waste Manag Assoc. 2024 Nov;74(11):783-803. doi: 10.1080/10962247.2024.2380333. Epub 2024 Aug 21.
9
Frequency and Impact of Summertime Stratospheric Intrusions over Maryland during DISCOVER-AQ (2011): New Evidence from NASA's GEOS-5 Simulations.“发现空气质量”(2011年)期间马里兰州夏季平流层侵入事件的频率与影响:来自美国国家航空航天局(NASA)GEOS - 5模拟的新证据
J Geophys Res Atmos. 2016 Apr 14;Volume 121(Iss 7):3687-3706. doi: 10.1002/2015JD024052.
10
Assessment of tropospheric ozone simulations in a regional chemical transport model using GEOS-Chem outputs as chemical boundary conditions.利用GEOS-Chem输出作为化学边界条件,在区域化学传输模型中评估对流层臭氧模拟。
Sci Total Environ. 2024 Jan 1;906:167485. doi: 10.1016/j.scitotenv.2023.167485. Epub 2023 Oct 5.

本文引用的文献

1
Augmenting the Standard Operating Procedures of Health and Air Quality Stakeholders With NASA Resources.利用美国国家航空航天局的资源强化卫生与空气质量相关利益者的标准操作程序。
Geohealth. 2021 Sep 1;5(9):e2021GH000451. doi: 10.1029/2021GH000451. eCollection 2021 Sep.
2
Description of the NASA GEOS Composition Forecast Modeling System GEOS-CF v1.0.美国国家航空航天局地球观测系统成分预测建模系统GEOS-CF v1.0的描述。
J Adv Model Earth Syst. 2021 Apr;13(4):e2020MS002413. doi: 10.1029/2020MS002413. Epub 2021 Apr 7.
3
COVID-19 Crisis Reduces Free Tropospheric Ozone Across the Northern Hemisphere.
新冠疫情危机降低了北半球对流层的自由臭氧含量。
Geophys Res Lett. 2021 Mar 16;48(5):e2020GL091987. doi: 10.1029/2020GL091987. Epub 2021 Feb 26.
4
Evaluation of NASA's high-resolution global composition simulations: Understanding a pollution event in the Chesapeake Bay during the summer 2017 OWLETS campaign.美国国家航空航天局高分辨率全球成分模拟评估:了解2017年夏季切萨皮克湾OWLETS活动期间的一次污染事件。
Atmos Environ (1994). 2020 Feb 1;222. doi: 10.1016/j.atmosenv.2019.117133. Epub 2019 Nov 16.
5
Tropospheric Emissions: Monitoring of Pollution (TEMPO).对流层排放:污染监测(TEMPO)
J Quant Spectrosc Radiat Transf. 2017 Jan;186:17-39. doi: 10.1016/j.jqsrt.2016.05.008. Epub 2016 Jun 6.
6
Quantifying TOLNet Ozone Lidar Accuracy during the 2014 DISCOVER-AQ and FRAPPÉ Campaigns.在2014年DISCOVER-AQ和FRAPPÉ活动期间对TOLNet臭氧激光雷达精度进行量化。
Atmos Meas Tech. 2017 Oct 4;10(10):3865-3876. doi: 10.5194/amt-10-3865-2017. Epub 2017 Oct 23.
7
Assessment of upper tropospheric and stratospheric water vapor and ozone in reanalyses as part of S-RIP.作为平流层-对流层相互作用研究计划(S-RIP)一部分,对再分析资料中对流层上部和平流层水汽及臭氧的评估。
Atmos Chem Phys. 2017 Oct;17(20):12743-12778. doi: 10.5194/acp-17-12743-2017. Epub 2017 Oct 26.
8
Stratospheric intrusion-influenced ozone air quality exceedances investigated in the NASA MERRA-2 Reanalysis.利用美国国家航空航天局(NASA)的现代-era回顾性分析研究与应用-2(MERRA-2)再分析数据,对平流层侵入影响下的臭氧空气质量超标情况进行了调查。
Geophys Res Lett. 2017 Sep 7;44(20):10691-10701. doi: 10.1002/2017gl074532. Epub 2017 Oct 28.
9
Frequency and Impact of Summertime Stratospheric Intrusions over Maryland during DISCOVER-AQ (2011): New Evidence from NASA's GEOS-5 Simulations.“发现空气质量”(2011年)期间马里兰州夏季平流层侵入事件的频率与影响:来自美国国家航空航天局(NASA)GEOS - 5模拟的新证据
J Geophys Res Atmos. 2016 Apr 14;Volume 121(Iss 7):3687-3706. doi: 10.1002/2015JD024052.
10
Reanalysis intercomparisons of stratospheric polar processing diagnostics.平流层极地过程诊断的再分析比对
Atmos Chem Phys. 2018;18(18):13547-13579. doi: 10.5194/acp-18-13547-2018. Epub 2018 Sep 25.