Mesoscale ensemble weather prediction at U.S. Army Dugway Proving Ground, Utah

Jason C. Knievel, Yubao Liu, Thomas M. Hopson, Justin S. Shaw, Scott F. Halvorson, Henry H. Fisher, Gregory Roux, Rong Shyang Sheu, Linlin Pan, Wanli Wu, Joshua P. Hacker, Erik Vernon, Frank W. Gallagher, John C. Pace

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

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 DPG use 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.

Original languageEnglish
Pages (from-to)2195-2216
Number of pages22
JournalWeather and Forecasting
Volume32
Issue number6
DOIs
StatePublished - Dec 1 2017

Keywords

  • Atmosphere
  • Complex terrain
  • Ensembles
  • Mesoscale models
  • Numerical weather prediction/forecasting
  • Operational forecasting

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