Distributed collaborative adaptive sensing for hazardous weather detection, tracking, and predicting

Abstract

A new data-driven approach to atmospheric sensing and detecting/ predicting hazardous atmospheric phenomena is presented. Dense networks of small high-resolution radars are deployed with sufficient density to spatially resolve tornadoes and other dangerous storm events and overcome the earth curvature-induced blockage that limits today's ground-radar networks. A distributed computation infrastructure manages both the scanning of the radar beams and the flow of data processing by dynamically optimizing system resources in response to multiple, conflicting end-user needs. In this paper, we provide a high-level overview of a system architecture embodying this new approach towards sensing, detection and prediction. We describe the system's data rates, and overview various modes in which the system can operate. © Springer-Verlag 2004.