Predicting Climate Regime Change in Chaotic Convection

A toy climate analogous to the famous Lorenz system [1] is derived and compared to computational fluid dynamics (CFD) simulations in order to test new modeling techniques. In particular, methods of data assimilation and ensemble forecasting are used to predict regime changes and residencies in this toy climate. A climate “truth” is created using a finite-element simulation of a thermal convection loop, a physical apparatus designed to be the simplest model of convection in the Earth’s atmosphere. Forecasts of the climate are made using low-dimensional Lorenz-like models and synchronized to noisy observations of the truth using various Kalman filters. Forecasting of regime changes has been successfully demonstrated when the same model is used to create both the observations and the forecast [2], but never for realistic chaotic convection.