Session 7.4 A Polar-Coordinate Real-Time Three-Dimensional Rapidly Updating Merger Technique for Phased Array Radar Scanning Strategies

Wednesday, 8 August 2007: 9:00 AM
Hall A (Cairns Convention Center)
Valliappa Lakshmanan, CIMMS/Univ. of Oklahoma, NOAA/NSSL, Norman, OK; and K. D. Hondl

Presentation PDF (2.3 MB)

Unlike conventional Doppler radar used operationally in the United States by the National Weather Service (WSR-88D) and the Federal Aviation Authority (TDWR), the National Weather Radar Testbed (NWRT) phased array radar will not be operated in fixed volume coverage patterns. Instead, the phased array radar will attempt to simultaneously maximize the utility of several possible uses, such as 3D storm analysis, area surveillance and aircraft tracking. In order to do so, the phased array radar will employ adaptive scanning, choosing to scan areas with storms in higher spatial and temporal resolution, meteorologically uninteresting areas with lower spatial and temporal resolution and interspersing a few beams to track any aircraft that have been identified.

To a downstream visualization program or automated severe-weather detection algorithm operating on phased array radar data, the incoming stream will be randomly organized in space and time. It is up to the application to create a coherent view of the atmosphere from the phased array radar beams.

In this paper, we describe a method of creating such a coherent view. In polar coordinates, this involves creating a rapidly updated "virtual volume scan". The virtual volume scan is created at the resolution appropriate to the use to which it will be put (0.1 degree spacing in elevation and azimuth and 500m in range, in the examples demonstrated in this paper) and will be created by treating each of the phased array radar range gates as "intelligent agents" that place themselves in the resulting polar grid, know how to collaborate with other agents to create optimal estimates of the radar values (both reflectivity and velocity) at each range gate of the virtual volume and know when they have either been superseded or are too old. The strategy used to create this optimal value is application and product specific.

The resulting virtual volume, created in real-time, is used by the downstream applications. This enables the downstream applications to work with a regularly spaced grid that is created at periodic intervals. Examples of PPIs, CAPPIs, RHIs and vertical slices of the resulting 3D virtual volume are demonstrated. Products resulting from a few example severe-weather analysis applications are also demonstrated.

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