Thursday, 4 June 2009: 4:00 PM
Grand Ballroom East (DoubleTree Hotel & EMC - Downtown, Omaha)
Presentation PDF (356.9 kB)
This paper describes an operational mesoscale ensemble numerical weather prediction system in use at the Dugway Proving Ground, or DPG. The primary DPG mission is to conduct testing of military materiel, and most of this testing occurs outdoors. Typically these tests have specific constraints on meteorological conditions for optimal testing, such as wind speed, temperature, moisture, precipitation, lightning, etc. Very accurate weather forecasts are required to plan and execute tests efficiently. High resolution modeling grids and customized mesoscale modeling are needed due to the strong influence of local terrain characteristics. Historically, a single numerical forecast (either MM5 or WRF) was used to forecast conditions 12-48 hours in advance of a test. In order to provide a level of confidence that forecast weather conditions will occur, DPG has installed and is using operationally a 30-member mesoscale ensemble. The ensemble system is based on the Four-Dimensional Weather (4DWX) system, developed by the National Center for Atmospheric Research in support of the U.S. Army's Research Development Test & Evaluation meteorology program, and is therefore referred to as E-4DWX. The 30 ensemble members are created by varying initial conditions, lateral boundary conditions, model physical parameterizations, and underlying land-surface characteristics. Additionally, the NWP model core is also varied with half using WRF and the other half using MM5. E-4DWX is currently running continuously at Dugway Proving Ground UT, using a 65 node computer provided by the High Performance Computing Modernization Program Office. The system generates four ensemble model runs per day. Forecast products are posted on a public website for access by forecasters. This paper will discuss the configuration of the E-4DWX system and the forecast products, and will show examples of how these products assist the forecaster in test support decisions.
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