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The Joint Doppler Operational Project was a cooperative inter-agency program directed toward the evaluation of recent advances in Doppler weather radar technology for operational applications by the participating agencies. The first two years of testing demonstrated the decisive superiority of Doppler techniques, in comparison with conventional methods, for reliable identification and early warning of tornadoes and other severe thunderstorm hazards. During the final year, the program evaluated the format and effectiveness of manually aided automatic display products transmitted in near-real time to operational agencies remotely located from the radar. Experiences of operating personnel utilizing these new techniques provide input toward system definition of NEXRAD, the Next Generation Weather Radar network now under development. One of the most encouraging examples of the enhanced warning capability realized by the remote transmission of the automated Doppler format was a successful forecast of severe weather for an Air Force Base which was a crucial factor in saving a fleet of aircraft from severe hail damage.
A storm tracking algorithm designed to detect and track fine structure in digitized radar data is evaluated. These fine structures are defined by regions containing values within 3 dB of peaks in reflectivity factor. The algorithm describes storm structure and evolution by correlating these peak regions in time and space. The evaluation consists of a comparison of the algorithm output with raw data and with output from an AFGL algorithm which detects and tracks three-dimensional reflectivity weighted centroids defined by a preselected threshold. It is concluded that the algorithm cannot reliably detect and track significant structures within storms when applied to data sets with a temporal resolution of aprox. 6 min and a spatial resolution of 1.0 deg in azimuth and 0.7 deg in elevation. The significance of tracking 3 dB peaks is questioned and the implication of defining a larger peak threshold is discussed. The algorithm does track the large features of storms with results similar to the AFGL algorithm. However, it does not run in real time and is not modular, unlike the AFGL algorithm.