The Engineering Research Center for Collaborative Adaptive Sensing of the Atmosphere (CASA) is creating a paradigm for severe weather warning systems based on low-power, low-cost networks of radars. These radar networks collect high spatial and temporal resolution data in the lower troposphere by adaptively scanning the atmosphere based on user needs for data and on the evolving weather. CASA has deployed a prototype system test bed in southwest Oklahoma, with radars, IT infrastructure, and a pilot group of users. An assessment of the Oklahoma test bed capabilities was conducted during the 2007 severe weather season from April to June. The CASA spring experiment evaluated the end-to-end system from adaptive sensing, optimization algorithms, and visualization software, to real-time dissemination of data to National Weather Service forecasters and emergency managers.

This paper will describe the results of CASA's participation in NOAA's first Experimental Warning Project where NWS forecasters from around the country provided feedback on CASA system design through the evaluation of real-time data and case studies from the Oklahoma test bed, and the completion of questionnaires. The goal was to understand how CASA data might impact NWS severe weather decision making in light of existing sources of weather information, forecaster interaction with technology, and societal considerations. Key advantages of CASA data include the ability to observe fine scale rotations close to the ground, and the ability to evaluate the vertical structure of a storm feature quickly. It also emerged that new conceptual models of warning, which link the new data to potential impacts, will need to be developed for CASA data.