Optimal sampling strategies for hazardous weather detection using networks of dynamically adaptive Doppler radars

In this paper, we explain our methods to determine the optimal adaptive scanning strategies for The Center for Collaborative Adaptive Sensing of the Atmosphere (CASA) radars in order to extract the maximum amount of information for a particular purpose while minimizing the resources used. CASA is a National Science Foundation Engineering Research Center that was created in fall 2003 and is led by the University of Massachusetts at Amherst with several partners including the University of Oklahoma. CASA is establishing a revolutionary new paradigm in which systems of distributed, collaborative, and adaptive sensor (DCAS) networks are being developed to overcome fundamental limitations in current approaches – particularly the inability to sample the lower parts of the atmosphere.

In the first phase of its research program, CASA is placing test beds of small, inexpensive, low-power Doppler weather radars – sited on existing infrastructures such as cell phone towers – to test the DCAS concept. The first such network, called NETRAD and consisting of 4 dual-polarization, mechanically-scanning Doppler radars, will begin operating in central Oklahoma in fall 2005. This network will be expanded to 9 phased-array radars in late 2006. Unique to these systems is their ability to dynamically adjust their scanning strategies and other attributes, in a collaborative manner with neighboring radars, to sense multiple atmospheric phenomena while simultaneously meeting multiple end user needs – all in a theoretically optimal manner.

In order to find out how to optimally sample with the CASA radars, we will be modeling tornadoes, mesocyclones, and other storm features with idealized flows, such as a Burgers-Rott vortex, and then fitting the observations (initially simulated data) to these models. Many scanning strategies will be devised with varying parameters such as the azimuthal sampling interval, the distance from the radar to the center of the vortex, and the number of radars adaptively scanning both a single vortex as well as more than one vortex. In order to determine which scanning strategy is optimal, metrics for optimality, such as cost functions and probability density functions will be used.