Publications

A key product within the Integrated Terminal Weather System (ITWS) Initial Operating Capability (IOC) product suite removes anomalous propagation (AP) ground clutter from the ASR-9 precipitation product. This has been identified as a critical component of ITWS due to the frequent occurrence of AP when storms or outflows move over an ASR-9. Editing is accomplished by comparing the raw ASR-9 weather data to composite maps generated by the Next Generation Weather Radar (NEXRAD) and the Terminal Doppler Weather Radar (TDWR). An editing template, containing regions of AP, is created based on the ASR-9 data collected at the middle of the composite volume scan to minimize the difference in update rates. The template is used to edit the ASR-9 scan immediately after the composite map and all subsequent scans until a new composite map is received. This algorithm has been shown to perform quite well, especially if the weather and AP returns are not co-located. During the 1994 Demonstration and Validation Operational Test and Evaluation in Memphis (MEM) and Orlando (MCO), the probability of editing AP (PEAP) in the absence of weather was 0.97 for level 2 and greater returns (Klingle-Wilson, 1995). The probability of editing weather (PEW) for those cases with weather only was quite low, i.e., 0.01. In order to minimize the removal of weather returns in those cases where the AP and weather are located in close proximity, the editing thresholds are quite conservative. This is reflected by the 1994 results which show a PEAP of 0.81 and a PEW of 0.02 for this class of event. Besides the conservative thresholds, another area of concern is the fact that the AP regions can expand or increase in intensity after the AP editing template is created. This rapid variation frequently occurs with convectively generated AP and can cause the performance of the algorithm to decrease with time until a new template is created. In this study, we will examine the algorithm failure mechanisms in detail to identify possible site-adaptable parameter changes that can be used to improve the performance for the mixed weather/AP events. This is especially germane since the parameter set was not re-evaluated after the TDWR composite map was incorporated in 1995. In the critical region over the airport during hazardous weather conditions, this radar updates more frequently than the NEXRAD. Since the parameters were designed to account for the NEXRAD volume update rate, they are probably too conservative for the current algorithm (which uses both composite maps).

An important limitation of precipitation sensors is contamination from ground clutter targets under conditions of anomalous propagation (AP). This problem can be mitigated significantly by high-pass clutter filters such as used by the Terminal Doppler Weather Radar (TDWR) and Next Generation Weather Radar (NEXRAD) systems....MIT Lincoln Laboratory (MIT/LL) has developed and tested an algorithm that removes AP from the NEXRAD reflectivity data. In this paper, we will first provide a brief description of the algorithm. Next we will present the truthing methodology used to identify AP. Then, we will show the algorithm performance results and failure mechanisms with this initial version. Finally, we consider refinements to improve the algorithm's performance.

Air traffic management is a challenging task, especially if the airspace involved is impacted by inclement weather. The high volume of air traffic which inundates the nation's major airports compounds the difficulties with which Air Traffic Control (ATC) specialists have to cope. When you add the unpredictability of thunderstorm growth and decay to the controllers workload, air traffic management becomes even more of a challenge. ATC specialists would benefit from reliable forecasts of thunderstorm growth and decay. To determine how they would use a Growth and Decay product, ATC specialists from the Memphis Air Route Traffic Control Center (ARTCC), Traffic Management Unit (TMU), and TRACON supervisors were interviewed while viewing five movie loops of Memphis weather cases. The movies consisted of the ASR-9 six-level reflectivity data, aircraft beacons, and storm motion vectors.

The Federal Aviation Administration (FAA) is currently deploying Terminal Doppler Weather Radars (TDWRs) at key airports in the continental U.S. that experience high volumes of traffic and high frequencies of thunderstorm impact. The TDWR is designed to display the location and intensity of storm cells as well as the location and intensity of wind shear events in the airport vicinity. The TDWR system uses clutter filters and four data quality editing techniques: point target removal, clutter residue editing maps (CREMs), range obscuration editing, and velocity dealiasing in an attempt to reduce base data contamination prior to wind shear algorithm processing. The performance of the wind shear detection algorithms is directly related to the quality of the base data. In particular, failures of the data quality editors can seriously degrade the wind shear detection algorithm's performance. It will be shown that these failures can lead to both undetected and false events. In addition, clutter contamination from nonmeteorological sources such as birds can produce false wind shear signatures in the radar data. This paper will examine the impact of data contamination on algorithm performance at key TDWR sites where base and products data have been collected. The severity of these failures will be discussed, along with possible solutions to the most significant problems.