7B.3 A Realtime Weather-Adaptive 3DVAR Analysis and WRF model Forecast System with Automatic Storm Positioning and On-demand Capability

Tuesday, 8 November 2016: 2:00 PM
Pavilion Ballroom West (Hilton Portland )
Yunheng Wang, CIMMS, Norman, OK; and J. Gao, T. A. Jones, D. M. Wheatley, K. H. Knopfmeier, G. J. Creager, L. J. Wicker, and J. S. Kain

A real-time, weather-adaptive three-dimensional variational data assimilation (3DVAR) system and a real-time forecast system with WRF model have been developed recently for the NOAA supported Warn-on-Forecast project (WoF). The goal for this work is to provide physically-consistent gridded analysis and forecast products to forecasters to help make their warning decisions in a timely manner. First, a storm positioning program is implemented based on NSSL WDSS-II two-dimensional composite reflectivity product. So it has the ability to automatically detect severe local hazardous weather events. Furthermore, the analysis and forecast can also be performed with on-demand capability in which end-users (e.g., forecasters or scientists) set up the location of the analysis and forecast domain in real time based on the current weather situation. Second, the 3DVAR system incorporates available mesoscale forecasts, radar, satellite retrieved cloud water path, and traditional observations to perform a rapid analysis. The above two procedures have been well tested in the past several years (Gao et al. 2013, Smith et al. 2014). Recently, an interface for linking this 3DVAR system with the WRF model has been developed. So the analysis can be used for initializing the WRF model. This enhanced system has been tested during the 2016 Hazardous Weather Testbed (HWT) Spring Experiment period. Two types of products are generated.  The first one, an analysis every 5 minutes has been produced with a floated weather-adaptive domain covered 640 km by 640 km. Then, a forecast has been launched every half hour for a 3-h forecast. The performance of the system during the 2016 Spring Experiment period will be reported during the conference.
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