The Center for Collaborative Adaptive Sensing of the Atmosphere (CASA), a National Science Foundation Engineering Research Center, is creating a new paradigm for weather observation using networks of low-power, low-cost radars that dynamically adapt their sensing strategies based on user needs for information and evolving weather. These radar systems map wind and rain in the lower troposphere, a region currently undersampled by current technology, and disseminate real-time, high spatial (250 meter) and temporal (1 minute) resolution data to decision makers, such as National Weather Service (NWS) forecasters and emergency managers.

This paper describes the development of an Integrated Systems Model (ISM), an end-to-end decision model of the CASA system linking “upstream” technical capabilities, such as targeted radar observations, to their incremental impacts on later “downstream” responses such as warning decisions, risk communication, public response, and the resulting socio-economic impacts. The goal of this project is three-fold: i) to determine the incremental socio-economic value of CASA data based on changes in user decision making; ii) to create socio-economic measures that can be incorporated into CASA's adaptive scanning strategies and iii) to utilize socio-economic valuation to guide longer term system design and deployment strategies. The ISM will model decisions related to severe thunderstorms and tornadic events, and consist of 4 linked sub-decision models: the adaptive observation decision by the CASA system, the NWS warning decision, emergency manager deployment and notification decisions, and public response related to impacts. Research and validation of the model occurs through simulation environments and through CASA's proof-of-concept test bed, a four radar network covering a 7,000 square kilometer region in southwest Oklahoma. The structure of the ISM will be described using a severe storm event that occurred on May 8, 2007 in the CASA test bed, including process and phenomena research for severe weather, socio-economic research and applications, and the integration of these into the evolving engineering design of a new observation system.