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An ensemble assessment of regional ozone model uncertainty with an explicit error representation

机译:带有明确误差表示的区域臭氧模型不确定度的整体评估

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摘要

In this paper, we examine the extent to which an ensemble generated from a single air quality model correctly represents the global uncertainty of ozone simulations with a regional scale chemistry-transport model and whether it is suitable for ozone data assimilation. An ensemble of 30 members is constructed from a reference simulation in which the model parameters that are the most uncertain for determining ozone concentrations are randomly perturbed. Comparisons of the simulated ensemble using the model CHIMERE with observations are examined over the summer season both at the surface and higher in the troposphere. Although the ensemble overestimates vertical and horizontal correlation between errors, the average model error is well represented both at the surface and in the vertical dimension (after an adjustment for the latter). A variability of about 7-8 ppb is found. The results found in this study with respect to tropospheric ozone model errors and error correlation lengths both from ensemble simulations and model to observation comparisons are of particular interest for data assimilation when constructing model error covariance matrices.
机译:在本文中,我们研究了从单个空气质量模型产生的整体正确表示区域规模化学迁移模型所代表的臭氧模拟的全球不确定性的程度,以及它是否适合臭氧数据同化。由参考模拟构建了一个由30个成员组成的集合,在该集合中,随机地扰乱了确定臭氧浓度最不确定的模型参数。在夏季,对流层和对流层较高处,使用CHIMERE模型将模拟集合与观测资料进行了比较。尽管整体高估了误差之间的垂直和水平相关性,但平均模型误差在表面和垂直尺寸上都得到了很好的表示(对后者进行调整之后)。发现约7-8 ppb的变异性。在研究中发现的有关对流层臭氧模型误差以及从整体模拟和模型到观测比较的误差相关长度的结果对于构建模型误差协方差矩阵时的数据同化特别有意义。

著录项

  • 来源
    《Atmospheric environment》 |2011年第3期|p.784-793|共10页
  • 作者单位

    CNRS, UMR 7583. Universites Paris-Est et Paris Diderot, Laboratoire Inter-Universitaire des Systemes Atmospheriques, LISA/IPSL, Creteil, France ,UPMC Univ. Paris 06 Universite Versailles St-Quentin CNRS/INSU, UMR 8190, IATMOS-IPSL, Paris, France ,National Center for Atmospheric Research, Atmo-pheric Chemistry Division, Boulder, CO, USA;

    rnCNRS, UMR 7583. Universites Paris-Est et Paris Diderot, Laboratoire Inter-Universitaire des Systemes Atmospheriques, LISA/IPSL, Creteil, France;

    rnCNRS, UMR 7583. Universites Paris-Est et Paris Diderot, Laboratoire Inter-Universitaire des Systemes Atmospheriques, LISA/IPSL, Creteil, France;

    rnInstitut National de l'Environnement Industriel et des Risques, Division des Risques Chroniques, Pare Technologique Alata, Vemeuil-en-Halatte, France;

    rnLaboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, laboratoire CEA/CNRS/UVSQ, Gif-sur-Yvette, France;

    rnCNRS, UMR 7583. Universites Paris-Est et Paris Diderot, Laboratoire Inter-Universitaire des Systemes Atmospheriques, LISA/IPSL, Creteil, France;

    rnCNRS, UMR 7583. Universites Paris-Est et Paris Diderot, Laboratoire Inter-Universitaire des Systemes Atmospheriques, LISA/IPSL, Creteil, France;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    ensemble method; ozone; modelling; error covariance; data assimilation;

    机译:合奏法臭氧;造型;误差协方差数据同化;

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