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Mesoscale Ensemble Weather Prediction at US Army Dugway Proving Ground, Utah

机译:Mesoscale Ensemble天气预报在美国陆军戴韦证明地面,犹他州

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摘要

Since 2007, meteorologists of the U.S. Army Test and Evaluation Command (ATEC) at Dugway Proving Ground (DPG), Utah, have relied on a mesoscale ensemble prediction system (EPS) known as the Ensemble Four-Dimensional Weather System (E-4DWX). This article describes E-4DWX and the innovative way in which it is calibrated, how it performs, why it was developed, and how meteorologists at DPGuse it. E-4DWX has 30 operational members, each configured to produce forecasts of 48 h every 6 h on a 272-processor high performance computer (HPC) at DPG. The ensemble's members differ from one another in initial-, lateral-, and lower-boundary conditions; in methods of data assimilation; and in physical parameterizations. The predictive core of all members is the Advanced Research core of the Weather Research and Forecasting (WRF) Model. Numerical predictions of the most useful near-surface variables are dynamically calibrated through algorithms that combine logistic regression and quantile regression, generating statistically realistic probabilistic depictions of the atmosphere's future state at DPG's observing sites. Army meteorologists view E-4DWX's output via customized figures posted to a restricted website. Some of these figures summarize collective results-for example, through means, standard deviations, or fractions of the ensemble exceeding thresholds. Other figures show each forecast, individually or grouped-for example, through spaghetti diagrams and time series. This article presents examples of each type of figure.
机译:自2007年以来,乌拉德探险地面(DPG)的美国陆军测试和评估指挥(ATEC)的气象学家依靠称为集合四维天气系统(E-4DWX)的Mescle集合预测系统(EPS) 。本文介绍了e-4dwx和它校准的创新方式,它如何表现,为什么它是如何开发的,以及如何DPGUSE的流星学家。 E-4DWX有30个操作成员,每个运营成员都配置为在DPG的272处理器高性能计算机(HPC)上每6小时生产48小时的预测。集合的成员在初始,横向和下边界条件下彼此不同;在数据同化的方法中;和物理参数化。所有成员的预测核心是天气研究和预测(WRF)模型的高级研究核心。最有用的近表面变量的数值预测通过结合逻辑回归和量子回归的算法动态校准,在DPG观察网站上产生大气未来状态的统计逼真的概率描绘。陆军气象学家通过定制数字查看E-4DWX的输出,发布到受限制的网站。其中一些图总结了集体结果 - 例如,通过均值超过阈值的均值,标准偏差或分数。其他图以通过意大利面条图和时间序列分别地示出了每个预测或分组 - 例如。本文提出了每种类型的例子。

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