1. National Weather Radar Testbed (NWRT) Oversight Panel and Spring 2007 Research Goals Jeff Kimpel and Doug Forsyth National Severe Storms Lab March 20, 2007

2. National Weather Radar Testbed (NWRT) Milestones Created NWRT Assessment Panel as required by the Navy/FAA/NOAA MOA and the NOAA/OU MOA –NOAA – Jeff Kimpel, Douglas Forsyth –FAA – James Williams, Bill Benner (Garth Tarok) –Navy – Ron Ferek, Scott Sandgathe –OU – Mark Yeary, Robert Palmer

3. NWRT Milestones (cont.) Developed procedures for requesting access to the NWRT http://www.nssl.noaa.gov/research/radar/nwrt_use.php Intent is to charge only for costs exceeding basic NWRT support.

4. 2007 National Weather Radar Testbed Projects Short DescriptionPrimary GoalsWeather Phenomena Requirements NWRT, Doug Forsyth Leader of NWRT Adaptive scanning & radar client interface, Dave Priegnitz Using phased array technology, a user has the capability to rapidly scan targets of interest as well as performing the traditional volume scan. The RCI and RTC software can be modified to satisfy these capabilities. Continue to update the RCI and RTC software to meet data collection needs. In addition, continue to develop an interface so that an algorithm(s) can be used to control radar scanning (future). All types of weather phenomena need to be supported by the system. The RCI client needs to be updated to support user needs as they are defined. Data collection, Ric Adams Operations during specified weather events and storage of collected data sets for analysis. Implementation and testing of upgraded software and hardware components. Capture at least one event for each of the weather phenomena requested. Moving the system forward in a thoughtful but accelerated process. As requested or any determined to be severe and within our collection boundaries. Operational system, working raids, and cooperative weather. Beam multiplexing & PAR support, Chris Curtis Support research on Staggered PRT beam multiplexing and ground clutter data collection  Collect first trip data from one beam position using a short PRT  Collect ground clutter data from different terrain types with varying wind conditions Limited to first trip in some direction with minimal change over time (ground clutter, clear air, and stratiform) Simple single PRT, single beam position scanning strategy, Multi-packet scanning strategy to collect large number of pulses (1024) at each beam position Oversampling and Whitening, Staggered PRT, Sebastian Torres Design, implementation, and testing of advanced weather radar signal processing techniques for the NWRT Collect snapshots of weather and clear-air data to support testing of signal processing techniques under development Widespread echoes and clear air Time series data with and without range oversampling, with and without staggered PRT.

5. Data display development, Kurt Hondl Display of MPAR/NWRT data sets, including base data, derived data, and algorithm/product data generated from the base data. Ensure that the data display needs of researchers are met. All weather phenomena (and non-weather phenomena such as aircraft tracks) will be researched using the display tools. No specific data collection requirements, but knowledge of base data and derived product formats will need to be coordinated. NWS liaison: Severe weather warning decision making R&D, Greg Stumpf Support HWT warning scale activities; provide information to MDL and AWIPS groups at HQ.  Observe the use of 2D and 3D displays of PAR data in the context of NWS warning decision making.  Support for development and evaluation of severe weather algorithms utilizing PAR data. All types of weather phenomena, but specifically those related to deep convection. Quick adaptation of scanning strategies to maximum best collection of data from particular phenomena NWS Pre-proof-of- concept experiment, Pam Heinselman On potentially high-impact severe weather days, provide data to NWS by running PAR and displaying data in HWT  Build NWS experience using PAR data & display capabilities during operations  Assess impacts (inc. lack thereof) of PAR data on operations Severe convective storms, w/ emphasis on: Tornado vortex signa. Mesocyclones Downbursts/microbursts Straight-line winds  Ability to scan adaptively in continuous manner  NWS accuracy of estimates  Surveillance and optimal strategies for phenomena’s scale & distance from radar Algorithm work, Travis Smith New warning decision- making guidance applications Develop storm interrogation and warning guidance applications that take advantage of high temporal sampling of potentially severe storms All types of severe convective storms (supercells, lines, isolated "pulse" storms, convective clusters)  radial sampling must be contiguous  full storm volume sampled every 30 seconds or less  0.5 to 1.0 degree sampling in vertical and horizontal Refractivity fields, Bob Palmer Retrieve refractivity fields (~moisture) using rapid update of PAR. Real-time implementation using avg I/Q and WDSS-II. Provide several case studies useful for CI studies. Compare to refractivity fields from KTLX. Days with potential for CI. Need to observe before (few hours) CI. Also interested in storm evolution effects due to moisture field Time series data. Avg I/Q ok if ready by spring. Full time series more flexible and preferred.  Prestorm: 360  coverage, 0.5  elev,  2 pulses  3 days of 24hr data  90  coverage during storms  Update cycle TBD

6. Transverse wind, Dick Doviak Implement and test the concept of Weather Radar Interferometry using a switched receiver to alternately sample sum and difference signals To measure cross beam wind, angular shear, and turbulence within and along the radar beam. Stratiform weather; having strong vertical shear. Rapid switch connected to the sum/difference channels (one data set with elevation difference another with azimuth difference). Time series data. Sector scans to the north and over the Kessler Farm site at few elevation angles. Mechanical and electronic scans, long dwell times. Tracking aircraft, Mark Yeary Using the PAR to detect aircraft. Based on detections, this would be ingested by a tracker to ultimately make one-step-ahead predictions for optimum beamsteering. Tracks should also be compared with ASR-9 data from the Will Rogers airport in OKC. A detailed study of weather phenomena and aircraft tracking is not currently available and needs to occur. It would be best if both convective storms and aircraft could be monitored simultaneously. Since each target requires different dwell parameters, optimal settings could be determined. The current hardware is sufficient; however, monopulse capabilities would be appreciated. Low number of pulses Few low-altitude scans (0  2 km) Update cycle TBD Coord. w/ refractivity project SMART-R validation & assimilation, Lou Wicker & Mike Biggerstaff Use both SMART-R to collect coordinated data sets with MPAR setting up 2 dual- Doppler networks in OKC area (40 km baselines), see attached graphic. Coordinate SMART radars to collect dual-Doppler data to be used for verification of MPAR data in assimilation experiments and MPAR cross-beam winds All type of convective weather, emphasis on severe convective lines and supercells Operational dates: 1 May to 1 June. 30-60 minute periods of MPAR collecting volumetric data at 30 second intervals coordinated with SR’s. Abt 10 events is optimal Interested in high resolution spatial sampling in horiz and vert. (up to 35 tilts) Radar coordinator involved in multiple projects, Don Burgess Interface between MPAR and other projects: WSR- 88D applications, WSR-88D data quality, and VORTEX2 preparation (Mobile radar) Compare MPAR data to WSR-88D baseline and experimental data, and to mobile radar data All types of data with emphasis on severe convection and supercells Emphasis on April and May storms Operating system with data collection that results in data that can be displayed in polar/constant elevation angle format

7. 19:40:0519:44:57 19:49:4919:54:42 Strong outflow at 19:56:00 Weak outflow in corresponding velocity field at 19:51:03 Strong updraft indicated by weak echo region Rapid descent of high reflectivity core MPAR MPAR vs. NEXRAD Scan Rate: Microburst Event NEXRAD MPAR captures 29 clear images and more data during the time it takes NEXRAD for 4, the result is better forecasts and earlier warnings