The End User Integration thrust is leading a new multi-disciplinary research effort to create an integrated decision model of CASA's end-to-end system (Integrated Systems Model) through a supplemental grant award. This Integrated Systems Model (ISM) will quantitatively link “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 ISM will enable incorporation of socio-economic considerations into the end user policy and resource allocation algorithms, and also permit measurement of how different DCAS capabilities reduce negative socio-economic impacts.

In January 2007, a multidisciplinary group of CASA researchers representing all thrusts, ESEAB members, National Weather Service forecasters, Oklahoma Emergency Managers, and a television meteorologist participated in a two-day workshop to begin to define the detailed research plan. The ISM will model decisions related to severe thunderstorms, including hail and straight line winds, and tornadic events within the Oklahoma Test Bed between the time a watch is issued until an event or false alarm occurs. The research and validation of the model will occur through the Oklahoma Test Bed, through weather simulations, and by leveraging existing end user research on public response and operational forecaster decision making. The ISM will consist 4 of mathematically linked sub-decision models: DCAS resource optimization, NWS warning, EM decisions, and public response related to impacts. The inputs and outputs to the sub-models are weather information: the attributes of weather data, such as feature strength, geographic specificity, or update time; and the quality/uncertainty of the data assessed by performance measures such as probability of detection (POD), false alarm rate (FAR), and lead time; and the manner in which the information is communicated. The supplement grant primarily funds the addition of decision scientists to the team, and expertise in the economic impacts and the measures that will link the models.