92nd American Meteorological Society Annual Meeting (January 22-26, 2012)

Tuesday, 24 January 2012: 5:00 PM
Developing Quality Control Techniques for a CONUS-Wide Multi-Year Radar-Derived Rotation Track Climatology
Room 357 (New Orleans Convention Center )
Madison L. Miller, NSSL/CIMMS/Univ. of Oklahoma, Norman, OK; and V. Lakshmanan and T. M. Smith
Manuscript (1.6 MB)

The Multi-Year Reanalysis Of Remotely-Sensed Storms (MYRORSS) project is a cooperative effort between the National Oceanic and Atmospheric Administration's (NOAA) National Severe Storms Laboratory (NSSL) and the National Climatic Data Center (NCDC) to reconstruct and evaluate numerical model output and radar products derived from 16 years of WSR-88D data over the CONUS. Several years of a hail climatology using the Maximum Estimated Size of Hail (MESH) parameter have already been processed and a rotation track climatology is nearly ready to begin processing.

The rotation track fields are created by using the local, linear, least squares derivative (LLSD) algorithm to produce the azimuthal shear field (Smith and Elmore 2004). After performing quality-control on the reflectivity field and stamping out azimuthal shear areas not associated with at least 40 dBZ, an azimuthal shear range-correction is applied. Data from multiple radars are then merged together to form two-dimensional low-level (0-3 km) and mid-level (3-6 km) maximum azimuthal shear fields. These maximum azimuthal shear fields are accumulated over time to create rotation tracks.

Due to the inherent noisiness of velocity-derived fields, a great deal of quality control is needed before process the rotation track climatology. Even small non-meteorological contaminants can become large problems when accumulated over time. To quality control the azimuthal shear fields, the wind field from a 20-km Rapid Update Cycle model (RUC) point sounding at each radar site is used as a first guess for the WSR-88D velocity dealiasing algorithm. Clusters of shear in the maximum azimuthal shear fields then are isolated using hysteresis segmentation. Multiple Hypothesis Tracking (MHT) techniques are then used to identify and associate these segments throughout time. A cost function based on size difference, segment proximity, and other factors is used to determine the ranked k-best associations. The associations with the lowest cost functions are then made and unassociated segments, usually non-meteorological contaminants, are pruned.

Applications of these quality control techniques and preliminary rotation track climatology results will be discussed.

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