A Point Cloud Method for Retrieval of High-Resolution 3D Gridded Reflectivity from Weather Radar Networks for Air Traffic Management

Abstract

AbstractA prototype high-resolution (1 km, 5 min) multiradar 3D gridded reflectivity product, including a suite of derived 2D vertical column products, has been developed for the Single European Skies Air Traffic Management Research program. As part of this, a new method for mapping radar data to grid points is being used, based on the concept of a binary space partitioning (BSP) tree that treats radar data as a set of points in a 3D point cloud. This allows the resulting analysis to be based on a complete picture of the nearby data from overlapping radars and can easily adapt to irregular grid configurations. This method is used with a Barnes successive corrections technique to retrieve finescale features while avoiding problems of undersmoothing in data-sparse regions. This has been tested using 3D domains enclosing the terminal maneuvering areas surrounding Paris, France, and London, United Kingdom, and using reflectivity plan position indicator scan data from the French and U.K. operational networks, encoded using the standard European Operational Programme for the Exchange of Weather Radar Information (OPERA) Data Information Model format. Quantitative intercomparisons between the new method, in various configurations; a high-resolution version of an existing method, in operational use at Météo-France; and a method that was developed by the National Oceanic and Atmospheric Administration for use with the Weather Surveillance Radar-1998 Doppler radar network, have been done using simulated radar scans derived from 3D synthetic radar reflectivity fields in stratiform and convective regimes.