Radar Data Quality Control And A 3Dvar Method For Wind And Thermodynamic Field Retrieval

Modern Doppler radars have the ability to scan large volumes of the atmosphere at high spatial and temporal resolutions. High-resolution radar measurements have provided unprecedented opportunities for high-resolution weather analyses and model initialization. However, the application of Doppler radar wind measurements is limited by the following problems: (1) there are various radar data quality problems, such as, data noise, range folding and velocity aliasing, anomalous propagation and ground clutter, and contamination due to biological flying objects;(2) the radar wind are not the regular numerical model variables, but limited to the velocity component in the direction of the radar beam.To improve the quality of raw radar data, various radar data quality problems are monitored by a real-time data ingest and graphical display system. Several data quality control parameters are identified and recorded using this real-time system. A probabilistic radar data quality control algorithm is developed based on statistic decision theory to identify and flag data quality problems using the quality control parameters. In particular, the method is applied to identify the contaminated radar observations by migrating birds. The algorithm is effective and computationally inexpensive. These properties are important for operational implementation.To extract more information from Doppler radar wind, a variational data assimilation method is developed to retrieve three-dimensional (3D) wind and thermodynamic fields from Dual-Doppler radar measurements. In this method, wind fields at the beginning and ending times of the data assimilation period and thermodynamic fields at the middle time of the data assimilation period are retrieved from two successive volume scans by using the weak form constraints provided by the mass continuity and momentum equations. The merits of the new method include: (1) both the evolution and advection of the observed radar wind are taken into account;(2) the retrieved winds can be compared with the radar observed radial winds in the cost-function at precisely the time and location of each radar beam;(3) the time tendency term in the momentum equations can be conveniently formulated and The performance of the new method is demonstrated by numerical experiments with simulated radar observations. The method is also applied to real radar data for a heavy rainfall event during the 2001 Meiyu season in China.