32nd Conference on Broadcast Meteorology/31st Conference on Radar Meteorology/Fifth Conference on Coastal Atmospheric and Oceanic Prediction and Processes

Friday, 8 August 2003: 4:45 PM
The identification and impact of AP/GC on quantitative precipitation estimates in mountainous terrain
Beth Clarke, CIMMS and NOAA/NSSL, Norman, OK; and S. Vasiloff
Poster PDF (306.5 kB)
The use of NSSL's Quantitative Precipitation Estimation and Segregation Using Multiple Sensors (QPESUMS) system for the estimation of precipitation in Arizona has lead to the identification of anomalous echo and persistent clutter in mountainous regions. These occurrences frequently lead to false precipitation accumulation. The two main locales that have experienced this 'Rain Rock' phenomenon are the White Mountains and the Harcuvar Mountains. Clutter from the White Mountains in east central Arizona is believed to be due to super-refraction of the lowest elevation angle, which causes the beam to encounter the mountains and return considerable signal back to the radar. Examples of AP/clutter from the White Mountain region on 1 January 2003 will be presented. During this event approximately 4 inches of precipitation accumulated over a 3 hr period. At 1612 UTC high reflectivities were identified over the White Mountains yet mysteriously disappeared without a trace by 1621 UTC, suggesting that the signal could be attributed to AP. The utility of a program that calculates the beam path based on refractive index gradients is being assessed. An analysis of clutter from the Harcuvar Mountains northwest of Phoenix will also be provided. It was discovered that range folded velocities prevent standard velocity-based removal techniques from fully migrating the clutter. The effectiveness of various techniques for AP/clutter removal on these terrain features will be discussed. These methods include those currently used in QPESUMS, a prototype AP/clutter removal technique that is at the developmental stage in QPESUMS, a new 'Hierarchical Texture Segmentation' technique, and the WSR-88D Radar Echo Classifier.

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