National Weather Radar Testbed (NWRT)Oversight Panel and Spring 2007 Research Goals

Jeff Kimpel and Doug Forsyth

National Severe Storms LabMarch 20, 2007

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

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.

2007 National Weather Radar Testbed Projects

Short Description Primary Goals Weather 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.

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.MesocyclonesDownbursts/microburstsStraight-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, 0.5elev, 2 pulses 3 days of 24hr data 90 coverage during storms Update cycle TBD

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 pulsesFew low-altitude scans (02 km)Update cycle TBDCoord. 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 supercellsOperational dates:1 May to 1 June.

30-60 minute periods of MPAR collecting volumetric data at 30 second intervalscoordinated with SR’s. Abt 10 events is optimalInterested 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 supercellsEmphasis on April and May storms

Operating system with data collection that results in data that can be displayed in polar/constant elevation angle format

19:40:05 19:44:57

19:49:49 19:54:42

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

MPAR vs. NEXRAD Scan Rate: Microburst Event

NEXRAD

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