Recent improvements in radar wind data quality control for data assimilation

This paper presents two recently developed and improved radar wind data quality control (QC) techniques for radar data assimilation applications. First, an automated technique is developed to identify and remove contaminated velocities by birds, especially migrating birds. This technique builds upon the existing hydrometeor classification algorithm (HCA) for dual-polarimetric WSR-88D radars developed at the NSSL, and it performs two steps. In the first step, the HCA is simplified and used to identify biological echoes (mainly from birds and insects). In the second step, a simple fuzzy logic method is developed to detect bird echoes among the biological echoes identified in the first step and thus remove bird-contaminated velocities. The method has been tested with polarimetric data collected from the operational KVNX and KICT radars during the 2011 fall and 2012 spring and fall migrating seasons. The simplified HCA has been incorporated into the operational radar reflectivity data QC package for radar data assimilation applications at NCEP. Second, the alias-robust variational analysis (Xu at al. 2012, JTech., 29, 1723–1729) is modified adaptively and used in place of the alias-robust velocity azimuth display (VAD) analysis (Xu at al. 2011, JTech., 28, 50–62) for all scan modes (including WSR-88D VCP31 with the Nyquist velocity reduced below 12 m/s and TDWR Mod80 with the Nyquist velocity reduced below 15 m/s), so more raw data can pass the stringent threshold conditions used by the reference check in the first step of Doppler velocity dealiasing in the NSSL radar wind data QC package. This improves the dealiased data coverage and still ensures the dealiased data to be free of false dealiasing, as required by radar data assimilation. This improvement has been incorporated into the NSSL radar wind data QC package and delivered to NCEP for further tests and radar data assimilation applications. The dealiasing technique is also improved by adding new procedures to the continuity check in the second step to increase the dealiased data coverage over storm-scale areas threatened by intense mesocyclones and their generated tornados. The detailed techniques and improved performances will be presented at the conference.