FAA Warning Applications
NSSL works with three other major laboratories as part of the Advanced Weather Radar Techniques (AWRT) Product Development Team (PDT). The goal of the AWRT PDT is to identify specific weather-related problems faced by the FAA and the National Airspace System and study how radar products, applications, or techniques that could help mitigate these problems.
Aviation weather hazard detection with polarimetric radar
Among the most appealing benefits to aviation users is the data quality improvement available from polarimetric radar over conventional radar. No other technique can match the ability to discriminate between meteorological and non-meteorological returns that polarimetric radars provide. Ground clutter, sea clutter, and anomalous propagation can all be alleviated through polarimetric techniques, even within precipitation echoes. Non-meteorological scatters, including birds or insects can be categorized to provide useful safety-of-flight information to controllers, or be eliminated.
Improved rain-snow discrimination, hail detection, estimation of heavy rainfall rates, and freezing-level designation are also capabilities demonstrated by polarimetric radar. Other benefits to aviation, likely to be developed long term, are improved quantification of winter (frozen) precipitation, detection of some mixed-phase icing conditions (especially situations involving embedded convection), the estimation of precipitation-impacted visibility, detection of lightning precursors, and improved microphysical parameterization in numerical forecast models. Polarimetric measurements should also be useful for eliminating regions of the atmosphere where particular hazards are not likely. The net result should be better detection and quantification of weather hazards in the terminal area and increased airport capacity.
Polarimetric Mixed-Phase Cloud Identification
A recent major thrust of the FAA-related dual-polarization research at NSSL was on substantial modification of the polarimetric classification algorithm. The new classification algorithm is designed to distinguish between 10 classes of radar echo: Ground clutter/anomalous propagation, biological scatterers, dry aggregated snow, wet snow, crystals, graupel, big drops, light and moderate rain, heavy rain, and hail.
This new scheme was tested on a number of cases, and the classification algorithm correctly recognized all important features in different areas of radar echo including gust front ahead of the squall line, hail, and graupel in the convective flank of the storm, rain – wet snow – dry snow – crystals gradual transition in the stratiform flank of the MCS, and anomalous propagation echoes behind the storms due to outflow of cold and moist air.
The Advanced Weather Radar and In-Flight Icing product development team winter weather polarimetric radar demonstration
During the 2006-2007 cold season, the AWRT PDT, in conjunction with the In-Flight Icing product development team will demonstrate polarimetric radar capabilities for aviation applications. Specifically, the prototype WSR-88DP radar, KOUN, operated at the National Severe Storms Laboratory in Norman, OK, will be used to demonstrate polarimetric capability for aviation-oriented cold-weather algorithms and techniques. The demonstrated capabilities will include hydrometeor classification, liquid/frozen hydrometeor discrimination, freezing level detection, visibility estimation, and quantitative precipitation estimation for winter precipitation. Research aircraft involvement is likely.
High-Resolution National 3-D Radar Mosaic
The AWRT PDT has implemented an enhanced National 3D radar mosaic that is updated every 5 min in real time and is developing new applications for polarimetric radar specific to aviation needs. Radar (conventional and polarimetric) input to numerical models initialization is under consideration, as are new methods of evaluating the depth of the convective boundary layer in real time.
WARP
The Weather and Radar Processor (WARP) is integral to air traffic controller displays. WARP now uses a radar designed specifically for weather applications. NSSL is working on new approaches to data quality control so users have confidence in the weather data products on display.
Reflectivity quality control procedure
NSSL continues the identification and archive of events associated with radar reflectivity quality control (QC). The QC events are used to test the effectiveness of QC applications to remove and/or mitigate the presence of non-meteorological radar returns. Specifically, we attempt to identify and archive radar data and other observational datasets for situations where non-meteorological returns would result in unrealistic portrayals of storm structure within the high-resolution national 3-D radar mosaic.
