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Community-wide validation of geospace model ground magnetic field perturbation predictions to support model transition to operations

机译:社区范围内对地理空间模型地面磁场扰动预测的验证,以支持模型过渡到运营

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摘要

In this paper we continue the community-wide rigorous modern space weather model validation efforts carried out within GEM, CEDAR and SHINE programs. In this particular effort, in coordination among the Community Coordinated Modeling Center (CCMC), NOAA Space Weather Prediction Center (SWPC), modelers, and science community, we focus on studying the models’ capability to reproduce observed ground magnetic field fluctuations, which are closely related to geomagnetically induced current phenomenon. One of the primary motivations of the work is to support NOAA SWPC in their selection of the next numerical model that will be transitioned into operations. Six geomagnetic events and 12 geomagnetic observatories were selected for validation. While modeled and observed magnetic field time series are available for all 12 stations, the primary metrics analysis is based on six stations that were selected to represent the high-latitude and mid-latitude locations. Events-based analysis and the corresponding contingency tables were built for each event and each station. The elements in the contingency table were then used to calculate Probability of Detection (POD), Probability of False Detection (POFD) and Heidke Skill Score (HSS) for rigorous quantification of the models’ performance. In this paper the summary results of the metrics analyses are reported in terms of POD, POFD and HSS. More detailed analyses can be carried out using the event by event contingency tables provided as an online appendix. An online interface built at CCMC and described in the supporting information is also available for more detailed time series analyses.
机译:在本文中,我们继续在GEM,CEDAR和SHINE计划中进行的全社区严格的现代空间天气模型验证工作。在这项特殊的工作中,在社区协调建模中心(CCMC),NOAA太空天气预报中心(SWPC),建模人员和科学界之间的协调下,我们专注于研究模型再现观测到的地面磁场波动的能力,即与地磁感应电流现象密切相关。这项工作的主要动机之一是支持NOAA SWPC选择将转换为运行状态的下一个数值模型。选择了6个地磁事件和12个地磁观测站进行验证。尽管对所有12个站点都可以使用建模和观测的磁场时间序列,但主要指标分析是基于六个代表高纬度和中纬度位置的站点进行的。为每个事件和每个站点建立了基于事件的分析和相应的权变表。然后使用列联表中的元素来计算检测概率(POD),错误检测概率(POFD)和Heidke技能评分(HSS),以严格量化模型的性能。本文以POD,POFD和HSS的形式报告了度量分析的摘要结果。可以使用作为事件附录的事件应急表作为在线附录进行更详细的分析。 CCMC内置的在线界面(在支持信息中进行了描述)也可用于更详细的时间序列分析。

著录项

  • 来源
    《Space Weather》 |2013年第6期|369-385|共17页
  • 作者单位

    The Catholic University of America, Physics Department, Washington, District of Columbia, USA., NASA Goddard Space Flight Center, Greenbelt, Maryland, USA.;

    NASA Goddard Space Flight Center, Greenbelt, Maryland, USA.;

    NASA Goddard Space Flight Center, Greenbelt, Maryland, USA.;

    Space Weather Prediction Center, NOAA, Boulder, Colorado, USA.;

    Space Weather Prediction Center, NOAA, Boulder, Colorado, USA.;

    Center for Space Science and Engineering Research, Virginia Polytechnic Institute and State University, Blacksburg, Virginia, USA.;

    Department of Atmospheric, Oceanic, and Space Sciences, University of Michigan, Ann Arbor, Michigan, USA.;

    Department of Atmospheric, Oceanic, and Space Sciences, University of Michigan, Ann Arbor, Michigan, USA.;

    Department of Atmospheric, Oceanic, and Space Sciences, University of Michigan, Ann Arbor, Michigan, USA.;

    High Altitude Observatory, National Center for Atmospheric Research, Boulder, Colorado, USA.;

    Space Science Center & Physics Department, University of New Hampshire, Durham, New Hampshire, USA.;

    Department of Computational and Data Sciences, George Mason University, Fairfax, Virginia, USA.;

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

    Predictive models; Magnetosphere; Data models; Magnetic recording; Meteorology; Plasmas; Computational modeling;

    机译:预测模型;磁气圈;数据模型;磁记录;气象学;等离子;计算模型;

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