Planet-in-a-bottle: A numerical fluid-laboratory system

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, and refines the mesh to better predict the future course of the fluid experiment. In addition, the feedback loop between targeting of both the observational system and mesh refinement will be mediated, if desired, by human control. © Springer-Verlag Berlin Heidelberg 2007.