11A.4 Four-Dimensional Variational Data Assimilation of High-resolution Radar Observations from CASA Dallas-Fort Worth (DFW) Urban Demonstration Network

Thursday, 14 January 2016: 11:30 AM
Room 348/349 ( New Orleans Ernest N. Morial Convention Center)
Renzo Bechini, Colorado State University, Fort Collins, CO; and V. Chandrasekar, J. Sun, and H. Chen

The Dallas Fort Worth (DFW) Urban Demonstration Network project is centered on the deployment of a network of several dual-polarization, X-band radars to demonstrate improved hazardous weather forecasts, warnings and response in a densely populated urban environment (pop. 6.3 million in 2010). Specifically, low level wind analysis and forecast ranging from 10 minutes to 3 hours are among the main research areas of the project. The scanning strategy of the radars is inherited from the CASA project distributed collaborative adaptive sensing concept and is intended to sample with high time resolution the lower atmosphere (1-3 km above ground level). During standard operation, 4 or more full PPI at low elevation angles are performed within 1 minute.

The Variational Doppler Radar Analysis System (VDRAS) is an advanced data assimilation system specifically designed for ingesting Doppler weather radar observations. The system has been installed at many sites around the world and is typically running using long-range operational S-band or C-band radar networks. The core 4-dimensional data assimilation scheme is based on a cloud-scale model and typically considers a 12-15 minutes time window for the radar assimilation, with 1-3 km spatial resolution.

In this study we explore the feasibility of running VDRAS with rapid update (5 minutes), exploiting the frequent low-level sampling of the atmosphere available within the DFW network of X-band radars. The X-band observations complement the data available from the volume scanning KFWS NEXRAD radar, allowing more accurate three dimensional wind retrievals. In order to cope with strong path attenuation affecting X-band power measurements, a new blended algorithm for the estimation of the rain water mixing ratio is used, replacing the traditional reflectivity-based method.

- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner