Objective Optimization of Weather Radar Networks for Low-Level Coverage Using a Genetic Algorithm

James M. Kurdzo and Robert D. Palmer, 2012: Objective Optimization of Weather Radar Networks for Low-Level Coverage Using a Genetic Algorithm. J. Atmos. Oceanic Technol., 29, 807–821. doi: http://dx.doi.org/10.1175/JTECH-D-11-00076.1

The current Weather Surveillance Radar-1988 Doppler (WSR-88D) radar network is approaching 20 years of age, leading researchers to begin exploring new opportunities for a next-generation network in the United States. With a vast list of requirements for a new weather radar network, research has provided various approaches to the design and fabrication of such a network. Additionally, new weather radar networks in other countries, as well as networks on smaller scales, must balance a large number of variables in order to operate in the most effective way possible. To offer network designers an objective analysis tool for such decisions, a coverage optimization technique, utilizing a genetic algorithm with a focus on low-level coverage, is presented. Optimization is achieved using a variety of variables and methods, including the use of climatology, population density, and attenuation due to average precipitation conditions. A method to account for terrain blockage in mountainous regions is also presented. Various combinations of multifrequency radar networks are explored, and results are presented in the form of a coverage-based cost–benefit analysis, with considerations for total network