Implementation and Analysis of Networked Radar Refractivity Retrieval

Abstract

Abstract The surface-layer moisture field can be obtained by estimating the refractive index of air, measured in parts per million, and is referred to as refractivity. A technique to estimate the refractivity by using radar has been demonstrated experimentally using the measured change in phase from stationary ground targets. Recently, a new network-based algorithm was proposed within the Center for Collaborative Adaptive Sensing of the Atmosphere (CASA) as an alternative approach, especially when dealing with multiple radars. That work presented the algorithm and applied it to purely simulated data. The research presented here provides more detail and takes the new networked radar approach to the next level by independently validating and demonstrating the output with data collected during a refractivity field experiment in Colorado during the summer of 2006. The practical aspects of implementing the network-based algorithm are presented along with a more complete mathematical representation. The results are then compared with the previously fielded technique starting from the same filtered phase data. From this comparison, the authors conclude that the networked algorithm has potential for providing a good refractivity estimate from a radar network once some of its own shortcomings are addressed.