Abstract. Humanity’s understanding of the Earth’s weather and climate depends critically on accurate forecasting and state-estimation technology. It is not clear how to build an effective dynamic data-driven application system (DDDAS) in which computer models of the planet and observations of the actual conditions interact, however. We are designing and building a laboratory-scale dynamic data-driven application system (DDDAS), called Planet-in-a-Bottle, as a practical and inexpensive step toward a planet-scale DDDAS for weather forecasting and climate model. The Planet-in-a-Bottle DDDAS consists of two interacting parts: a fluid lab experiment and a numerical simulator. The system employs data assimilation in which actual observations are fed into the simulator to keep the models on track with reality, and employs sensitivity-driven observations in which the simulator targets the real-time deployment of sensors to particular geographical regions and times for maximal effect, an...
Chris Hill, Bradley C. Kuszmaul, Charles E. Leiser