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An Effective Configuration of Ensemble Size and Horizontal Resolution for the NCEP GEFS

机译:NCEP GEFS的合奏大小和水平分辨率的有效配置

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摘要

Two important questions are addressed in this paper using the Global Ensemble Forecast System (GEFS)from the National Centers for Environmental Prediction (NCEP):(1) How many ensemble members are needed to better represent forecast uncertainties with limited computational resources? (2) What is the relative impact on forecast skill of increasing model resolution and ensemble size? Two-month experiments at T126L28 resolution were used to test the impact of varying the ensemble size from 5 to 80 menbers at the 500-hPa geopotential height.Results indicate that increasing the ensemble size leads to significant improvements in the performance for all forecast ranges when measured by probabilistic metrics,but these improvements are not significant beyond 20 members for long forecast ranges when measured by deterministic metrics.An ensemble of 20 to 30 members is the most effective configuration of ensemble sizes by quantifying the tradeoff between ensemble performance and the cost of computational resources.Two representative configurations of the GEFS-the T126L28 model with 70 members and the T190L28 model with 20 members,which have equivalent computing costs-were compared.Results confirm that,for the NCEP GEFS,increasing the model resolution is more (less) beneficial than increasing the ensemble size for a short (long) forecast range.
机译:本文使用国家环境预测中心(NCEP)的全球整体预报系统(GEFS)解决了两个重要问题:(1)需要多少个集合成员才能以有限的计算资源更好地表示预测不确定性? (2)增加模型分辨率和集合大小对预测技能有什么相对影响?在T126L28分辨率下进行的为期两个月的实验用于测试在500 hPa的地势高度上将集合体大小从5改变为80的影响,结果表明,增加集合体的大小可以显着改善所有预报范围的性能。通过概率指标进行度量,但对于确定性指标进行度量时,对于较长的预测范围而言,这些改进不会超过20个成员。通过量化集成绩效与成本之间的权衡,由20到30个成员构成的集成体是最有效的集成体配置。比较了GEFS的两个代表性配置,即具有70个成员的T126L28模型和具有20个成员的T190L28模型,它们具有同等的计算成本。结果证实,对于NCEP GEFS,提高模型分辨率更多(更少)。 )有利于在较短(较长)的预测范围内增加总体规模。

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  • 来源
    《大气科学进展(英文版)》 |2012年第4期|782-794|共13页
  • 作者单位

    Key Laboratory of Meteorological Disaster of Ministry of Education,Nanjing University of Information Science & Technology, Nanjin9 210044;

    Environmental Modeling Center/NCEP/NOAA, Camp Springs, MD 20746, USA;

    UCAR, Boulder, CO 80307, USA;

    Environmental Modeling Center/NCEP/NOAA, Camp Springs, MD 20746, USA;

    I.M. Systems Group, Inc.(IMSG)at the Environmental Modeling Center/NCEP/NOAA,Camp Springs, MD 20746, USA;

    Key Laboratory of Meteorological Disaster of Ministry of Education,Nanjing University of Information Science & Technology, Nanjin9 210044;

  • 收录信息 中国科学引文数据库(CSCD);中国科技论文与引文数据库(CSTPCD);
  • 原文格式 PDF
  • 正文语种 chi
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