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An Assessment of the Performance of the Operational Global Ensemble Forecast Systems in Predicting the Forecast Uncertainty

机译:评估全球业务预报系统在预测不确定性方面的性能

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摘要

This study investigates the efficiency of the operational global ensemble forecast systems in capturing the spatiotemporal evolution of the forecast uncertainty. It has two novel aspects: first, it extends the results of an earlier study from 2012 to 2015; second, it documents the first attempts to predict the reliability of the ensembles in capturing the uncertain forecast features and the 95th percentile value of the forecast error for operational ensembles. It is found that the main characteristics of the systems of the different centers in their efficiency in representing the spatiotemporal evolution of the forecast uncertainty have not changed much in the last three years. The only exception is the UKMO ensemble, whose performance improved in predicting the total magnitude of the uncertainty, but greatly degraded in predicting the patterns of forecast uncertainty. All ensembles were found to have major difficulties with predicting the large scale atmospheric flow in the forecast range longer than 10 days. These difficulties are due to the inability of the models to maintain the large-scale zonal anomalies of the atmospheric flow in the long forecast range. It was also found that the flow-dependent reliability of the ensembles in capturing the local structure of the forecast uncertainty and the 95th percentile value of the forecast error can accurately be predicted.
机译:本研究调查了可操作的全球整体预报系统在捕获预报不确定性的时空演变方面的效率。它具有两个新颖的方面:首先,它将早期研究的结果从2012年扩展到2015年。第二,它记录了在捕获不确定的预测特征和操作集成的预测误差的第95个百分位值时预测集成的可靠性的首次尝试。发现在过去三年中,不同中心的系统在表示预测不确定性的时空演变方面的效率的主要特征没有太大变化。唯一的例外是UKMO合奏,其在预测不确定性的总大小方面的性能有所提高,但在预测预测不确定性的模式方面却大大降低了性能。发现所有合奏团在预测超过10天的预报范围内的大规模大气流量方面都存在重大困难。这些困难是由于模型无法在较长的预报范围内维持大范围的大气流量纬向异常所致。还发现,可以准确地预测集合体在捕获预测不确定性的局部结构和预测误差的第95个百分数值时与流量相关的可靠性。

著录项

  • 作者

    Loeser, Carlee Frances;

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  • 年度 2016
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  • 原文格式 PDF
  • 正文语种 en
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