We report on an ongoing effort to build a Dynamic Data Driven Application System (DDDAS) for short-range forecast of weather and wildfire behavior from real-time weather data, images, and sensor streams. The system changes the forecast as new data is received. We encapsulate the model code and apply an ensemble Kalman filter in time- space with a highly parallel implementation. In this paper, we discuss how we will demonstrate that our system works using a DDDAS testbed approach and data collected from an earlier fire.
Department, Program, or Center
Chester F. Carlson Center for Imaging Science (COS)
International Conference on Computational Science - ICCS 2006 3993 (2006) 522-529
RIT – Main Campus