Efficient visualization of weather radar 2D products in hail suppression information system

Hail suppression information systems must successfully solve two major problems: detecting hail threatening clouds and efficient seeding of the clouds. Accurate and efficient representation of clouds in real space is a crucial requirement for successful classification of the cloud as hail threatening. Data about clouds are collected by weather radar. Radar creates regular 3D data grid in spherical space, which imposes the problem of designing the method for converting obtained data to Cartesian space. In this paper, we propose new methods for 2D visualization of clouds that solve this problem keeping the performance high. Weather radar data are visualized in three orthogonal cross sections. Developed methods create cross section directly from spherical space, avoiding conversion of the part of 3D dataset into Cartesian space. This fact enabled fast and accurate visualization several meteorological 2D products. The methods incorporate the Earth's curvature and refraction of radar rays necessary to display weather radar data in real geographical space. Proposed methods are embedded in the HASIS 3D hail suppression system. They provide more efficient monitoring of situation in atmosphere and faster detection of hail threatening clouds. Furthermore, they improve precision of cloud parameters measurements and increase accuracy of cloud seeding zones extraction.