CMG: Improve the Computational Performance of Global Atmospheric Chemistry Models through Spatial Mechanism Reduction

CMG:通过空间机制还原提高全球大气化学模型的计算性能

基本信息

  • 批准号:
    0417810
  • 负责人:
  • 金额:
    $ 32.12万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2004
  • 资助国家:
    美国
  • 起止时间:
    2004-09-01 至 2007-08-31
  • 项目状态:
    已结题

项目摘要

The ability to model oxidant concentrations (ozone and OH) in the lower atmosphere (troposphere) is central to a wide range of environmental issues. It plays an essential role in addressing issues of air quality, aerosol and acid formation, and global budgets of greenhouse gases. Our fundamental understanding of the chemical factors controlling tropospheric oxidants is fairly well established, but the computational challenge of atmospheric modeling is enormous. Chemical mechanisms include hundreds of coupled chemical species reacting on timescales ranging from milliseconds to many years. The cost of solving the resulting stiff system of coupled differential equations in a global model is such as to prevent simulations of adequate spatial resolution or temporal extent. This computational difficulty hinders general progress in our ability to model atmospheric chemistry and to address related environmental issues. The problem will be exacerbated over the next decade as satellite observations provide vast amounts of data on atmospheric composition. Exploitation of these data will require fast models. Meeting this challenge requires substantial advances in both computational resources and numerical algorithms.The present project will improve numerical algorithms for describing oxidant chemistry in global models through the collaboration of an applied mathematician (Brenner) and an atmospheric chemistry modeler (Jacob). Our central idea is that most of the chemical complexity is confined to a relatively small atmospheric domain (chemical boundary layer) near the continental surface where emissions take place. There is thus the possibility of using a targeted reduction of the chemical mechanism in which a reduced set of reactants is used in the remote atmosphere and the full chemical mechanism is used in the chemical boundary layer. Implementation is complicated by the dynamic nature of the chemical boundary layer, the need to have different definitions of the chemical boundary layer for different chemical species, and the need for a matching procedure to accurately connect the two regimes. We expect that results from this project will significantly enhance the capabilities of global atmospheric chemistry models and in this manner will improve our ability to address a range of important environmental issues.
对低层大气(对流层)中的氧化剂浓度(臭氧和氢氧化氢)进行建模的能力是一系列环境问题的核心。它在解决空气质量、气溶胶和酸的形成以及全球温室气体预算等问题上发挥着至关重要的作用。我们对控制对流层氧化剂的化学因素的基本理解已经确立,但大气模拟的计算挑战是巨大的。化学机制包括数百个相互耦合的化学物种在从毫秒到数年的时间尺度上进行反应。在全球模型中求解所得到的刚性耦合微分方程组的成本是如此之高,以至于无法进行足够的空间分辨率或时间范围的模拟。这一计算困难阻碍了我们在建立大气化学模型和解决相关环境问题方面取得的普遍进展。随着卫星观测提供了大量关于大气成分的数据,这个问题在未来十年将会加剧。利用这些数据将需要快速的模型。应对这一挑战需要在计算资源和数值算法方面取得实质性进展。本项目将通过一位应用数学家(Brenner)和一位大气化学建模师(Jacob)的合作,改进在全球模型中描述氧化剂化学的数值算法。我们的中心思想是,大多数化学复杂性仅限于发生排放的大陆表面附近相对较小的大气区域(化学边界层)。因此,有可能采用有针对性的化学机制,即在遥远的大气中使用一组减少的反应物,而在化学边界层中使用完整的化学机制。由于化学边界层的动态性质,需要对不同化学物种的化学边界层有不同的定义,以及需要一种匹配程序来准确连接两个制度,因此执行起来很复杂。我们预计,该项目的成果将大大提高全球大气化学模型的能力,并以这种方式提高我们解决一系列重要环境问题的能力。

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

Daniel Jacob其他文献

Metabolite quantification data based on 1H-NMR profiling of eggplant or pepper fruit during its development
  • DOI:
    10.1186/s13104-024-06996-1
  • 发表时间:
    2024-11-13
  • 期刊:
  • 影响因子:
    1.700
  • 作者:
    Léa Roch;Catherine Deborde;Daniel Jacob;Anaïs Clavé;Marguerite Batsale;Yves Gibon;Annick Moing
  • 通讯作者:
    Annick Moing
From participatory to inclusive climate services for enhancing societal uptake
从参与性到包容性气候服务以增强社会吸收
  • DOI:
    10.1016/j.cliser.2021.100266
  • 发表时间:
    2021
  • 期刊:
  • 影响因子:
    3.2
  • 作者:
    D. Williams;Daniel Jacob
  • 通讯作者:
    Daniel Jacob
Using Qualitative Data Analysis to Measure User Experience in a Serious Game for Premed Students
使用定性数据分析来衡量医学预科学生严肃游戏中的用户体验
  • DOI:
    10.1007/978-3-319-39907-2_9
  • 发表时间:
    2016
  • 期刊:
  • 影响因子:
    0
  • 作者:
    M. Zielke;Djakhangir Zakhidov;Daniel Jacob;Sean Lenox
  • 通讯作者:
    Sean Lenox

Daniel Jacob的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('Daniel Jacob', 18)}}的其他基金

Collaborative Research: Development and Applications of GEOS-Chem Atmospheric Chemistry in CESM and MUSICA
合作研究:GEOS-Chem大气化学在CESM和MUSICA中的开发和应用
  • 批准号:
    2228359
  • 财政年份:
    2022
  • 资助金额:
    $ 32.12万
  • 项目类别:
    Standard Grant
The Tenth (10th) International GEOS-Chem Meeting (IGC10); Saint Louis, Missouri; June 7-10, 2022
第十届(10th)国际GEOS-Chem会议(IGC10);
  • 批准号:
    2218241
  • 财政年份:
    2022
  • 资助金额:
    $ 32.12万
  • 项目类别:
    Standard Grant
Collaborative Research: Integrating GEOS-Chem Atmospheric Chemistry into the Community Earth System Model (CESM)
合作研究:将 GEOS-Chem 大气化学整合到社区地球系统模型 (CESM) 中
  • 批准号:
    1914903
  • 财政年份:
    2019
  • 资助金额:
    $ 32.12万
  • 项目类别:
    Standard Grant
The Ninth International GEOS-Chem Meeting (IGC9); Cambridge, Massachusetts; May 6-9, 2019
第九届国际GEOS-Chem会议(IGC9);
  • 批准号:
    1855750
  • 财政年份:
    2019
  • 资助金额:
    $ 32.12万
  • 项目类别:
    Standard Grant
The Eighth International GEOS-Chem Meeting (IGC8); Cambridge, Massachusetts; May 1-4, 2017
第八届国际GEOS-Chem会议(IGC8);
  • 批准号:
    1659903
  • 财政年份:
    2017
  • 资助金额:
    $ 32.12万
  • 项目类别:
    Standard Grant
A Comprehensive Coupled Model for Tropospheric Halogen Chemistry: Evaluation of Impacts on Tropospheric Ozone, Hydroxyl Radical (OH), and Mercury
对流层卤素化学综合耦合模型:对对流层臭氧、羟基 (OH) 和汞影响的评估
  • 批准号:
    1643217
  • 财政年份:
    2016
  • 资助金额:
    $ 32.12万
  • 项目类别:
    Continuing Grant
Travel Support for Young Scientists to Attend the 7th International GEOS-Chem Meeting (IGC7) held at Harvard University; Cambridge, MA; May 4-7, 2015
资助年轻科学家参加在哈佛大学举行的第七届国际 GEOS-Chem 会议(IGC7);
  • 批准号:
    1459489
  • 财政年份:
    2015
  • 资助金额:
    $ 32.12万
  • 项目类别:
    Standard Grant
EAGER: Characterization of Surface Tension During the Western Atlantic Climate Study (WACS)
EAGER:西大西洋气候研究 (WACS) 期间表面张力的表征
  • 批准号:
    1252755
  • 财政年份:
    2012
  • 资助金额:
    $ 32.12万
  • 项目类别:
    Standard Grant
Collaborative Research: Type 1: LOI: L02170303: Arctic Climate Response to Decadal Changes in Radiative Forcing from Aerosols and Ozone
合作研究:类型 1:LOI:L02170303:北极气候对气溶胶和臭氧辐射强迫的十年变化的响应
  • 批准号:
    1049021
  • 财政年份:
    2011
  • 资助金额:
    $ 32.12万
  • 项目类别:
    Standard Grant
ETBC: Global 3-D Modeling of Atmospheric Mercury and its Coupling to the Ocean and Land: Impacts of Past and Future Anthropogenic Emissions
ETBC:大气汞及其与海洋和陆地耦合的全球 3-D 建模:过去和未来人为排放的影响
  • 批准号:
    0961357
  • 财政年份:
    2010
  • 资助金额:
    $ 32.12万
  • 项目类别:
    Standard Grant

相似海外基金

III: Small: Computational Methods for Multi-dimensional Data Integration to Improve Phenotype Prediction
III:小:多维数据集成的计算方法以改进表型预测
  • 批准号:
    2246796
  • 财政年份:
    2023
  • 资助金额:
    $ 32.12万
  • 项目类别:
    Standard Grant
Computational approaches to characterize heterogeneity and improve risk stratification in complex disease phenotypes
表征复杂疾病表型异质性并改善风险分层的计算方法
  • 批准号:
    10805689
  • 财政年份:
    2023
  • 资助金额:
    $ 32.12万
  • 项目类别:
Computational Studies to Improve Understanding and Outcomes of Covalent Labeling Mass Spectrometry Measurements
提高对共价标记质谱测量的理解和结果的计算研究
  • 批准号:
    2247002
  • 财政年份:
    2023
  • 资助金额:
    $ 32.12万
  • 项目类别:
    Standard Grant
A Novel computational approach to optimize Fontan and improve surgical predictability
一种优化 Fontan 并提高手术可预测性的新型计算方法
  • 批准号:
    10557238
  • 财政年份:
    2022
  • 资助金额:
    $ 32.12万
  • 项目类别:
A Novel computational approach to optimize Fontan and improve surgical predictability
一种优化 Fontan 并提高手术可预测性的新型计算方法
  • 批准号:
    10346020
  • 财政年份:
    2022
  • 资助金额:
    $ 32.12万
  • 项目类别:
Computational approaches to characterize heterogeneity and improve risk stratification in complex disease phenotypes
表征复杂疾病表型异质性并改善风险分层的计算方法
  • 批准号:
    10448966
  • 财政年份:
    2022
  • 资助金额:
    $ 32.12万
  • 项目类别:
Leveraging computational models of neurocognition to improve predictions about individual youths' risk for substance use disorders
利用神经认知的计算模型来改进对青少年个体物质使用障碍风险的预测
  • 批准号:
    10213907
  • 财政年份:
    2021
  • 资助金额:
    $ 32.12万
  • 项目类别:
HSI Implementation and Evaluation: Bridging the Gap: Designing a Technology Learning Community Integrating Computational Thinking to Improve STEM Engagement Across Disciplines
HSI 实施和评估:弥合差距:设计集成计算思维的技术学习社区,以提高跨学科的 STEM 参与度
  • 批准号:
    2122690
  • 财政年份:
    2021
  • 资助金额:
    $ 32.12万
  • 项目类别:
    Standard Grant
Leveraging computational models of neurocognition to improve predictions about individual youths' risk for substance use disorders
利用神经认知的计算模型来改进对青少年个体物质使用障碍风险的预测
  • 批准号:
    10382322
  • 财政年份:
    2021
  • 资助金额:
    $ 32.12万
  • 项目类别:
A computational approach for quantifying motor behaviors in spinocerebellar ataxias to improve early detection of motor signs and precisely estimate disease severity and disease change
一种量化脊髓小脑共济失调运动行为的计算方法,以改善运动体征的早期检测并精确估计疾病严重程度和疾病变化
  • 批准号:
    10609864
  • 财政年份:
    2021
  • 资助金额:
    $ 32.12万
  • 项目类别:
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了