The NCAR-ATEC 4D Weather (4DWX) Modeling System: Updates and New Developments

An operational 4DWX system, jointly developed by NCAR and the Army Test and Evaluation Command (ATEC), is the primary source of weather forecasts and analyses at seven US Army ATEC test ranges across United States. The core modeling technology of 4DWX is a Real-Time Four Dimensional Data Assimilation (RTFDDA) and forecasting system. RTFDDA was built around both the Penn State/NCAR Mesoscale Model version 5 (MM5) and the Weather Research and Forecasting (WRF) model. RTFDDA is capable of continuously collecting and ingesting diverse synoptic and asynoptic weather observations from conventional and unconventional platforms, and provides continuous 4-D weather analyses for accurate nowcasts and short-term forecasts for mesoscale regions. In addition to its critical role at ATEC test ranges RTFDDA also supports numerous other DoD, public, and private weather-critical applications. The observational data ingested by the system includes WMO standard upper-air and surface reports, wind profilers, satellite cloud-drift winds, commercial aircraft reports, all available mesonet data, radar observations, etc. In the last 2 year, the RTFDDA system has been expanded to include the following new modeling developments that significantly expand the 4DWX application capabilities: a) Ensemble-RTFDDA, which is a 30 member, operational, multi-model, cycling mesoscale ensemble data analysis and forecasting system that samples and propagates the uncertainties in the major components of RTFDDA; b) LES (Large Eddy Simulation) modeling, which is nested down from the RTFDDA mesoscale data assimilation and forecasts to LES models with grid intervals of ~100 m for meso-gamma regions using 30-m SRTM resolution terrain; c) Climate-FDDA, which produces micro-climatographies at ranges by running continuous FDDA for the last 30 years using coarse global analyses and all available observations; d) HRLDAS (High-Resolution Land-Surface Data Assimilation System), which assimilates high-resolution satellite vegetation and soil data to generate high-resolution, accurate states of soil moisture and temperature; and e) RTFDDA-WRFVAR hybrid data assimilation that effectively incorporates radar data and satellite radiance observations. A recent study evaluated the impact of using local rawinsonde data on the overall model solution accuracy. Example products and verification results will be presented to illustrate these new 4DWX modeling capabilities.